Data Scientist Jobs At Microsoft

LinkedIn is the world's largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters. This role will be based in Sunnyvale. At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what's best for you and when it is important for your team to be together. LinkedIn's Data Science team leverages big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to drive member engagement, business growth, and monetization efforts. With over 900 million members around the world, a focus on great user experience, and a mix of B2B and B2C programs, a career at LinkedIn offers countless ways for an ambitious data scientist to have an impact. We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. It is expected that this person understands experimentation and/or machine learning techniques to be able to implement from scratch and have the ability to extend and enhance these techniques to specific applications like business problems. Successful candidates will exhibit technical acumen on inference and algorithms, and the business savviness to use these technical skills to drive better business decision-making. Responsibilities: • Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities and develop algorithms and methodologies to address them. • Analyze large-scale structured and unstructured data. • Conduct in-depth and rigorous data science research, model improvement, advanced experiments, observational causal studies to quantify the cause and effect in the ecosystem, identify business opportunities and to drive member value and customer success. • Develop methodologies to enhance LinkedIn's product and platform capabilities. • Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights • Promote and enable adoption of technical advances in Data Science; elevate the art of Data Science practice at LinkedIn. • Improve LinkedIn's ability to measure and credibly speak to labor market trends and other economic phenomena. • Initiate and drive projects to completion independently • Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations and evangelize data-driven business decisions in support of strategic goals • Partner with cross-functional teams to initiate, lead or contribute to large-scale/complex strategic projects for team, department, and company • Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews Basic Qualifications: • Bachelor's Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc. • 3+ years of industry or relevant academia experience • Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl) • Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. R, Python) Preferred Qualifications: • BS and 5+ years of relevant work experience, MS and 3+ years of relevant work experience, or Ph.D. and 1+ years of relevant work/academia experience • MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc. Suggested Skills • Machine Learning • Research • Causal Inference You will Benefit from our Culture: We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $128,000.00 to $210,000.00 Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit ************************************** Equal Opportunity Statement LinkedIn is committed to diversity in its workforce and is proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: *********************************************************************************************************** Please reference ******************************************************************************************** and ************************************************************************************************ for more information. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: -Documents in alternate formats or read aloud to you -Having interviews in an accessible location -Being accompanied by a service dog -Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: ******************************** Global Data Privacy Notice for Job Candidates This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: ***************************************

Come build community, explore your passions, and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead. Data Scientists at Microsoft use machine learning, statistics, experiments, and more to build and improve great products while making business impact. **The Microsoft Datacenter Energy Strategy and Partnerships Team** identifies long term growth obstacles and develops global mitigation strategies, centralizing global functions to deliver consistency and scalability. This spans energy technology, resilience, commercial partnership, and business operations strategy. The **Energy System Modeler** on the Microsoft Datacenter Energy Strategy Team will be responsible for conducting and managing electricity grid studies and analyses to ensure energy infrastructure investment, development, and reliability to support the global growth of Microsoft's datacenters. You will demonstrate familiarity with a variety of grid models and studies, experience in conducting these studies and managing the development and outputs of such models, as well as identify business challenges and deliver insights needed to overcome them. You will develop a quantitative understanding of the energy infrastructure investments and policies needed to support Microsoft's continued datacenter growth. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. **Please note this application is only for roles based in our Redmond, Washington office. For roles in other offices in the United States, please see our Careers site (************************************ .** **Responsibilities** + Conduct analyses of energy system simulations and optimizations using state of the art commercial and open-source software, and communicate results in both reports/papers and presentations. + Research and develop energy system models to support Microsoft datacenter growth by identifying and expanding capacity, lowering costs, and reducing carbon emissions. Research and evaluate grid models and analyses of global energy industry markets, infrastructure, and technologies. + Leverage grid modeling and analysis to contribute to the development and maintenance of reliable and sustainable energy infrastructure to support datacenter operations and growth, identifying potential risks, efficiencies, and savings. + Translate business needs into scopes of work for grid modeling and analyses. Develop assumptions, inputs, and scenarios for models to inform transmission capacity availability, transmission planning, generation capacity expansion, transmission reliability/availability, and clean energy procurement strategy. + Interpret model results for cross-functional leadership. Propose business, investment, and operational recommendations informed by insights and backed by data. Work with energy regulatory policy leads to develop advocacy positions informed by grid analysis and company needs. + Ensure stakeholder alignment and identify and mitigate risks for assigned projects. Manage change, negotiate deadlines and deliverables with stakeholders, prioritize work, and advise management on status, under guidance. Consider cross-functional inputs and balances competing business objectives. Communicate content status and performance to cross-functional teams. Serve as a point of contact to answer questions, provide feedback, and review work. + Work with internal and external collaborators on topics including: + Demand flexibility + Reliability and resilience + Transmission expansion + Technology benefit and cost analysis + Projections of buildouts of generation, transmission, and energy storage + Electrification of transportation, building, and manufacturing **Qualifications** **Required Qualifications:** + Doctorate (or currently pursuing) in Operational Research, Industrial System Engineering, Electrical Engineering, Computer Engineering, Statistics, Econometrics, Computer Science, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research). **Preferred Qualifications:** + 2+ years of experience in electricity grid modeling and optimization, power system planning and operation, energy markets and regulation. Both academic research and industry experience are considered. + 2+ years of experience in developing and reviewing code using Python, Julia, or another contemporary high-level object-oriented programming language. + Industrial experience, whether as an intern or in full-time roles, within energy industry consulting firms, ISO/RTOs, power system software vendors, or utility companies highly preferred. + Experience with energy policy and regulatory analysis highly preferred. + Understanding of datacenter industry or other large industrial customers. + Ability to manage and prioritize multiple simultaneous projects with minimal direction. + Growth mindset with advanced problem-solving skills to see the opportunity for grid models to inform energy infrastructure development. + Experience with executive communication, adept at leveraging open communication and extensive stakeholder engagement to influence decisions and meet near and long-term goals. + 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers). + Experience or course work applying ML to a type of data and or used algorithms to conduct experiments on data. + Proficiency in using one or more programming or scripting languages to work with data such as: Python, Perl, or C#. Data Science IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $127,200 - $208,800 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: **************************************************** Microsoft will accept applications, and process offers for these roles on an ongoing basis. Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (************************************************************** .

Apply share * link Copy link * email Email a friend info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Cambridge, MA, USA; Atlanta, GA, USA; Austin, TX, USA; Seattle, WA, USA. Minimum qualifications: * Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience * 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis. * 4 years of experience in business visualization tools like Looker, Tableau, etc. Preferred qualifications: * Master's degree in Computer Science, Economics, or Mathematics, or a related field. * 5 years of work experience in data science or quantitative analytics with focus on statistical modeling, Machine Learning, and AI. * Experience with both SQL and Python. * Experience with Machine Learning, AI or AI Pipeline. * Experience in Google Cloud Platform. About the job Cloud Learning Services (CLS) is revolutionizing direct cloud learning. We empower users of all levels with interactive labs and guided experiences to build practical skills on Google Cloud Platform and other leading technologies. Our mission is to make the cloud accessible, engaging, and enjoyable to learn. As a Business Data Scientist, you will play a key role in uncovering valuable insights from diverse data sources to solve critical business tests. You will address a wide range of exciting projects, from establishing new measurement frameworks to identifying meaningful patterns in large datasets, ultimately empowering stakeholders to make data-driven decisions. In this role, you will need to be a detail-oriented problem-solver with a strong foundation in data analytics, data visualization, and Artificial Intelligence/Machine Learning. You will solve the real-world problems and a commitment to continuous learning. Exceptional communication and stakeholder management skills are essential, as you will collaborate extensively with cross-functional teams. If you succeed in dynamic environments and are eager to make a real impact with data, we encourage you to apply! The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities * Extract actionable insights from large, complex datasets and build data products like dashboards to operationalize them, driving measurable improvements in Key Performance Indicators (KPIs). * Present and communicate actionable insights and recommendations to executives, leaders, and cross-functional partners, including Product, Engineering, and Marketing teams. * Serve as a peer-reviewer and consultant to other members of the team, fostering a collaborative and knowledge-sharing environment. * Learn and share knowledge of the latest advancements in AI/ML and data science that are relevant to our work.

info_outline X This role may also be located in our Playa Vista, CA campus. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Ann Arbor, MI, USA; Atlanta, GA, USA; Austin, TX, USA; Chicago, IL, USA; Mountain View, CA, USA; New York, NY, USA; Los Angeles, CA, USA; San Francisco, CA, USA; Washington D.C., DC, USA. Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree. Experience with data science tech stack (e.g., Python) and database languages (e.g. SQL). Preferred qualifications: PhD degree in Computer Science, Statistics, or other relevant quantitative disciplines, or an equivalent amount of machine learning experience. Familiarity with reporting solutions, and visualization/dashboarding tools. Proven ability to translate ambiguous business needs into clear technical requirements for impactful data products. Ability to take initiative with excellent leadership and communication skills. Comfortable with engineering best practices, including developing BRDs/PRDs/Design Docs, code reviews, etc., ensuring analytical accuracy. About the job We are a data science team that use AI/ML to enable Google's people analytics strategy. We build AI solutions that empower people analysts and leaders to make data-driven decisions, and inspire People Analytics to be on the cutting-edge. We achieve this through a culture of continuous learning, sharing, and growth. This is a unique opportunity at Google to be at the forefront of applying AI/ML to solve complex people-analytics challenges at a global scale. In this role, you'll leverage Google's people data and cutting-edge technology to develop and deploy innovative solutions that directly impact Googlers' lives. You'll also play a crucial role in shaping the future of people analytics by collaborating with cross-functional teams, upskilling colleagues in AI/ML, and fostering a data-driven culture within people operations. This role offers the chance to make a real difference in the lives of Googlers while contributing to the advancement of AI/ML in the HR domain. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Design and implement robust data pipelines to collect, process, and transform complex and large data sets from various data sources. Develop various types of machine learning models, conducting model evaluation, and collaborating with engineering teams to deploy the models into a production environment. Develop and apply Natural Language Processing (NLP) models (such as sentiment analysis, topic modeling, etc.) to extract insights from unstructured text data. Collaborate with cross-functional teams within POps and HR Engineering organizations to understand the business problem, define project scope, gather the requirements, and develop ML solutions that address the problem effectively. Communicate technical concepts and findings to both technical and non-technical audiences, enabling POps stakeholders to make informed decisions about Googlers.

This role may also be located in our Playa Vista, CA campus. Minimum qualifications: + Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. + 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree. + Experience with data science tech stack (e.g., Python) and database languages (e.g. SQL). Preferred qualifications: + PhD degree in Computer Science, Statistics, or other relevant quantitative disciplines, or an equivalent amount of machine learning experience. + Familiarity with reporting solutions, and visualization/dashboarding tools. + Proven ability to translate ambiguous business needs into clear technical requirements for impactful data products. + Ability to take initiative with excellent leadership and communication skills. + Comfortable with engineering best practices, including developing BRDs/PRDs/Design Docs, code reviews, etc., ensuring analytical accuracy. We are a data science team that use AI/ML to enable Google's people analytics strategy. We build AI solutions that empower people analysts and leaders to make data-driven decisions, and inspire People Analytics to be on the cutting-edge. We achieve this through a culture of continuous learning, sharing, and growth. This is a unique opportunity at Google to be at the forefront of applying AI/ML to solve complex people-analytics challenges at a global scale. In this role, you'll leverage Google's people data and cutting-edge technology to develop and deploy innovative solutions that directly impact Googlers' lives. You'll also play a crucial role in shaping the future of people analytics by collaborating with cross-functional teams, upskilling colleagues in AI/ML, and fostering a data-driven culture within people operations. This role offers the chance to make a real difference in the lives of Googlers while contributing to the advancement of AI/ML in the HR domain. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google (************************************* . + Design and implement robust data pipelines to collect, process, and transform complex and large data sets from various data sources. + Develop various types of machine learning models, conducting model evaluation, and collaborating with engineering teams to deploy the models into a production environment. + Develop and apply Natural Language Processing (NLP) models (such as sentiment analysis, topic modeling, etc.) to extract insights from unstructured text data. + Collaborate with cross-functional teams within POps and HR Engineering organizations to understand the business problem, define project scope, gather the requirements, and develop ML solutions that address the problem effectively. + Communicate technical concepts and findings to both technical and non-technical audiences, enabling POps stakeholders to make informed decisions about Googlers. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also ******************************* and ************************************************************* If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: ***************************************

Apply share * link Copy link * email Email a friend info_outline X This role may also be located in our Playa Vista, CA campus. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Ann Arbor, MI, USA; Atlanta, GA, USA; Austin, TX, USA; Chicago, IL, USA; Mountain View, CA, USA; New York, NY, USA; Los Angeles, CA, USA; San Francisco, CA, USA; Washington D.C., DC, USA. Minimum qualifications: * Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. * 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree. * Experience with data science tech stack (e.g., Python) and database languages (e.g. SQL). Preferred qualifications: * PhD degree in Computer Science, Statistics, or other relevant quantitative disciplines, or an equivalent amount of machine learning experience. * Familiarity with reporting solutions, and visualization/dashboarding tools. * Proven ability to translate ambiguous business needs into clear technical requirements for impactful data products. * Ability to take initiative with excellent leadership and communication skills. * Comfortable with engineering best practices, including developing BRDs/PRDs/Design Docs, code reviews, etc., ensuring analytical accuracy. About the job We are a data science team that use AI/ML to enable Google's people analytics strategy. We build AI solutions that empower people analysts and leaders to make data-driven decisions, and inspire People Analytics to be on the cutting-edge. We achieve this through a culture of continuous learning, sharing, and growth. This is a unique opportunity at Google to be at the forefront of applying AI/ML to solve complex people-analytics challenges at a global scale. In this role, you'll leverage Google's people data and cutting-edge technology to develop and deploy innovative solutions that directly impact Googlers' lives. You'll also play a crucial role in shaping the future of people analytics by collaborating with cross-functional teams, upskilling colleagues in AI/ML, and fostering a data-driven culture within people operations. This role offers the chance to make a real difference in the lives of Googlers while contributing to the advancement of AI/ML in the HR domain. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities * Design and implement robust data pipelines to collect, process, and transform complex and large data sets from various data sources. * Develop various types of machine learning models, conducting model evaluation, and collaborating with engineering teams to deploy the models into a production environment. * Develop and apply Natural Language Processing (NLP) models (such as sentiment analysis, topic modeling, etc.) to extract insights from unstructured text data. * Collaborate with cross-functional teams within POps and HR Engineering organizations to understand the business problem, define project scope, gather the requirements, and develop ML solutions that address the problem effectively. * Communicate technical concepts and findings to both technical and non-technical audiences, enabling POps stakeholders to make informed decisions about Googlers.

As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Oculus). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond. Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem. Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them. Communication and influence: You won't simply present data, but tell data-driven stories. You will influence and convince upwards, downwards and horizontally to your partners using clear insights and recommendations. You will build credibility through structure, clarity and comprehensiveness, and be a trusted strategic partner. Currently has or in the process of obtaining Ph.D. in Mathematics, Statistics, a relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta. Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python) or statistical packages (e.g., R). Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment. Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta. Experience working with distributed computing tools (MapReduce, Hadoop, Hive, etc.). Experience working with large data sets. Experience manipulating and analyzing high-volume, high-dimensionality data from varying source.

As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Oculus). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond. Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem. Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them. Communication and influence: You won't simply present data, but tell data-driven stories. You will influence and convince upwards, downwards and horizontally to your partners using clear insights and recommendations. You will build credibility through structure, clarity and comprehensiveness, and be a trusted strategic partner. Currently has or in the process of obtaining Ph.D. in Mathematics, Statistics, a relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta. Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python) or statistical packages (e.g., R). Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment. Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta. Experience working with distributed computing tools (MapReduce, Hadoop, Hive, etc.). Experience working with large data sets. Experience manipulating and analyzing high-volume, high-dimensionality data from varying source.

HP is the world's leading personal systems and printing company. We create technology that makes life better for everyone, everywhere. Our innovation springs from a team of passionate, talented, and curious individuals, each collaborating and contributing their own perspectives, knowledge, and experience to advance the way the world works and lives. We are looking for visionaries, with a passion for learning, to join our Strategic Planning and Modelling (SPaM) Data Science team. Our team members are tasked with evaluating supply chain investment and improvement opportunities, generating strategic business recommendations, and creating next-generation predictive and prescriptive analytical model deployments. We provide technical and thought leadership as we partner with senior executives to set strategic direction and drive innovation in our global supply chain. HP's SPaM team draws upon a 35-year history of success in supply chain innovation, enjoys a flexible work schedule, and invests in our continued success through formal training and mentorship. Join SPaM, if pioneering data-based innovations to solve business challenges for HP sounds like fun to you! Responsibilities * Pair with SPaM team members and collaborate with cross-functional teams to frame business challenges, structure analytical approaches, gather key data, evaluate alternative solutions, and present well-supported conclusions to management * Develop and diffuse innovations in inventory management, working capital optimization, network design, forecasting, complexity reduction, product planning, manufacturing, distribution, and related areas * Effectively tell stories with data using visualization tools/methods to demonstrate insight, impact, and business value * Build, deploy, and support innovative predictive and prescriptive analytic solutions at scale * Use proven MOC techniques to ensure smooth adoption of new solutions * Maintain proficiency within the data science and supply chain management domains by keeping up with technology advancements Education and Experience Required * MS/PhD in a business analytics field (i.e. Industrial Engineering, Management Science, Operations Research, Statistics, Data Science) or MBA with Supply Chain or Operations concentration * Operational experience in one of the following: network design, inventory management, planning, forecasting, procurement, logistics, warranty, product quality, product variety management, or similar supply chain domain area * 10+ years experience Knowledge and Skills * Applied experience with machine learning and optimization on large datasets * Proficient with Python, SQL, GitHub Co-Pilot, ChatGPT, PowerBI, Excel * Experience with generative-AI * Passion for data science & delivering data-driven outcomes * Demonstrated innovation across the supply chain domains (Plan, Source, Make, Deliver) * Expertise with inventory optimization math and deployment of the mathematical formulas into a business process * Demonstrated practical experience in an operational environment * Experience implementing and handing off operational analytical solutions to business users * Demonstrated ability to deal well with ambiguity and work collaboratively in a fast-pace environment * Excellent problem solver * Demonstrated ability to communicate concisely with diplomacy, credibility, and confidence * Experience with data visualization and data presentation in a clear and effective manner * Experience leading, collaborating with, and delivering results in cross-functional teams * Familiarity with statistics, forecasting, simulation, advanced data visualization, spreadsheet modelling * A desire to be a part of the HP team with a commitment to build upon our brand that is synonymous with innovation, trust, reliability, and sustainability The base pay range for this role is $154,000 to $237,150 annually with additional opportunities for pay in the form of bonus and/or equity (applies to US candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: * Health insurance * Dental insurance * Vision insurance * Long term/short term disability insurance * Employee assistance program * Flexible spending account * Life insurance * Generous time off policies, including; * 4-12 weeks fully paid parental leave based on tenure * 11 paid holidays * Additional flexible paid vacation and sick leave (US benefits overview) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law.

HP is the world's leading personal systems and printing company. We create technology that makes life better for everyone, everywhere. Our innovation springs from a team of passionate, talented, and curious individuals, each collaborating and contributing their own perspectives, knowledge, and experience to advance the way the world works and lives. We are looking for visionaries, with a passion for learning, to join our Strategic Planning and Modelling (SPaM) Data Science team. Our team members are tasked with evaluating supply chain investment and improvement opportunities, generating strategic business recommendations, and creating next-generation predictive and prescriptive analytical model deployments. We provide technical and thought leadership as we partner with senior executives to set strategic direction and drive innovation in our global supply chain. HP's SPaM team draws upon a 35-year history of success in supply chain innovation, enjoys a flexible work schedule, and invests in our continued success through formal training and mentorship. Join SPaM, if pioneering data-based innovations to solve business challenges for HP sounds like fun to you! Responsibilities * Pair with SPaM team members and collaborate with cross-functional teams to frame business challenges, structure analytical approaches, gather key data, evaluate alternative solutions, and present well-supported conclusions to management * Develop and diffuse innovations in inventory management, working capital optimization, network design, forecasting, complexity reduction, product planning, manufacturing, distribution, and related areas * Effectively tell stories with data using visualization tools/methods to demonstrate insight, impact, and business value * Build, deploy, and support innovative predictive and prescriptive analytic solutions at scale * Use proven MOC techniques to ensure smooth adoption of new solutions * Maintain proficiency within the data science and supply chain management domains by keeping up with technology advancements Education and Experience Required * MS/PhD in a business analytics field (i.e. Industrial Engineering, Management Science, Operations Research, Statistics, Data Science) or MBA with Supply Chain or Operations concentration * Operational experience in one of the following: network design, inventory management, planning, forecasting, procurement, logistics, warranty, product quality, product variety management, or similar supply chain domain area * 7-10 years experience Knowledge and Skills * Applied experience with machine learning and optimization on large datasets * Proficient with Python, SQL, GitHub Co-Pilot, ChatGPT, PowerBI, Excel * Experience with generative-AI * Passion for data science & delivering data-driven outcomes * Demonstrated innovation across the supply chain domains (Plan, Source, Make, Deliver) * Expertise with inventory optimization math and deployment of the mathematical formulas into a business process * Demonstrated practical experience in an operational environment * Experience implementing and handing off operational analytical solutions to business users * Demonstrated ability to deal well with ambiguity and work collaboratively in a fast-pace environment * Excellent problem solver * Demonstrated ability to communicate concisely with diplomacy, credibility, and confidence * Experience with data visualization and data presentation in a clear and effective manner * Experience leading, collaborating with, and delivering results in cross-functional teams * Familiarity with statistics, forecasting, simulation, advanced data visualization, spreadsheet modelling * A desire to be a part of the HP team with a commitment to build upon our brand that is synonymous with innovation, trust, reliability, and sustainability The base pay range for this role is $136,850 to $210,750 annually with additional opportunities for pay in the form of bonus and/or equity (applies to US candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: * Health insurance * Dental insurance * Vision insurance * Long term/short term disability insurance * Employee assistance program * Flexible spending account * Life insurance * Generous time off policies, including; * 4-12 weeks fully paid parental leave based on tenure * 11 paid holidays * Additional flexible paid vacation and sick leave (US benefits overview) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law.

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ THE GROUP: AI is defining the next era of computing, and this is just the beginning. We see the benefits of AI every day-enabling medical research, curbing credit card fraud, reducing congestion in cities, or simply making life easier. In the ever-evolving landscape of artificial intelligence, we are a powerhouse - a cutting-edge 'AI Software Solutions Team'. Specialized in AI optimization, fine-tuning large language models to unlock unprecedented Generative AI efficiency. Our expertise extends beyond the hardware realm, encompassing 3P enablement, where we develop custom AI Software Solutions for Industry leading AI customers. Are you excited to work with one of Top 1% of the AI companies in the world? THE ROLE: This role will be part of the team of Data Scientists that are designing the next generation of ML and AI into the Enterprise Data Center GPU space. THE PERSON: We are looking for deep learning data scientists with proven record implementing models and AI solutions around computer vision, language models and/or reinforcement or recommender models. If you have experience in at least 2 of the 4, we are looking for you…. KEY RESPONSIBILITIES: * Understanding and prototyping customer AI workloads and working with optimization team on accelerating models for AMD infrastructure. * Delivering AI solutions in line with product roadmap on time with high quality. * Involved in cross function team interaction and engagement with various key players and stakeholders in the organization. * Play a role in all the phases of software & model development, from requirement gathering, analysis, design, development, testing and final release to customers. * Provide clear and timely communication related to status and other key aspects of the project to leadership team. * Responsible for working with customers and internal support teams for resolving critical customer escalations on a need basis. * Willingness to learn skills, tools, and methods to advance the quality, consistency, and timeliness of AMD software products. * Experience with deep learning models and associated AI frameworks (PyTorch, TensorFlow, Jax (FLAN)) PREFERRED EXPERIENCE: * Deep experience with AI/ML frameworks like Pytorch, Tensor flow, JAX, etc. is required. * Knowledge of Acceleration platforms like GPU, TPU, APU is required. PREFERRED ACADEMIC CREDENTIALS: * BS, MS, or PhD with several years of related experience in Computer Engineering or Electrical Engineering or Computer Science or related equivalent from top universities. LOCATION: Santa Clara, CA, Austin, TX, Bellevue, WA #LI-G11 #LI-HYBRID At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD's Employee Stock Purchase Plan. You'll also be eligible for competitive benefits described in more detail here. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.

The Red Hat Global Sales Go-To-Market Strategy & Incentives team is looking for an experienced Senior Principal Data Scientist to join our team. In this role you will apply your advanced analytic and data science skills to deliver insights that support go-to-market strategy development, which in turn positively impacts Red Hat's revenue generating programs and projects. You will use data to drive growth, enable high quality and more precise business decisions. This is to enable high quality data to manage the Sales Cadence, and end-to-end Quota Process Transformation, including seller profile, sales roles & measurements module. You will leverage your mathematical and statistical expertise, along with your natural curiosity and creativity, to mine and interpret data to address questions, connect the dots and uncover hidden opportunities to realize the data's full potential, slicing and dicing it to create new visions for the business. You must be bright and motivated with a balance of technical skills, business savvy, and strong interpersonal and communication skills to help build the next generation of data-driven action and decision making. What you will do: Designs and develops enterprise-class, advanced analytics models to understand and solve complex GTM business problems such as segmentation, quota modeling, resource deployment model creation and Cost of Sales/Sales Productivity. Identifies relevant data sources and sets to mine for customer/business opportunities, collecting large structured and unstructured datasets and variables. Leads the design, execution and interpretation of data/analytic studies, including algorithm development, sample size calculations, statistical method selection, model development/tuning, etc. Transform & improve data quality for all dimensions of Sales management & planning. Create data architecture aligned to the business requirements for Sales Management Curate data fit for purpose for end-to-end Incentives process, including target planning, quotas, development & territory structures Transform the end-to-end process for Quotas from client segmentation to target setting models for Quotas, Territory & Quota deployment at scale Develops processes utilized to perform data and error analysis to improve data modeling; ensures data is clean and validated for uniformity and accuracy to support consistent, meaningful reporting Analyzes data for trends and patterns and interpret data with clear objectives in mind. Collaboratively develops predictive and advanced intelligence to empower and optimize customer engagements at scale. Works closely with key leaders/teams across Sales, Finance, Operations, Marketing and IT, to understand business needs, empower business stakeholders to execute. Translates complex analytical and technical concepts to business stakeholders and executive leadership to enable understanding and guide informed business decision making. Serves as a lead, overseeing the work of other Data Analysts on the team, serving as a SME across different functional aspects of the work this team undertakes. Leverage judgment and interpretative understanding of the data to help resolve critical issues that will have an impact on the long term success of the business. Apply learnings from the data, alongside proven theories and concepts, to advise Red Hat executives on proposed strategies and strategy adjustments What you will bring: 15+ years experience manipulating data sets and building statistical models. Experience working in or directly with Sales teams in a software/technology company. Advanced experience in pattern recognition and predictive modeling. Familiarity with business value and use cases of data science concepts such as artificial intelligence and machine learning. Knowledge of advanced statistical techniques and concepts (regression, simulation, scenario analysis, clustering, decision trees, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Ability to take initiative, manage multiple projects and problem solve in ambiguous situations. Excellent written and verbal communication skills, for use in information gathering, presenting findings and coordinating across teams. A drive to learn and master new technologies and techniques. Motivated with a solid sense of accountability. Experience with SQL and programming languages (e.g., Java/Python, SAS, R) Experience with relational database systems like SQL Server, Amazon Redshift, Oracle, Big Query, etc. Bachelor's degree (or equivalent) in statistics, mathematics, computer science, data science or a quantitative related field; Master's degree strongly preferred. The following are a plus: Experience using Tableau and Google productivity suite (e.g., Docs, Sheets, Slides). Experience with Salesforce.com (SFDC) and reporting in SFDC The salary range for this position is $131,420.00 - $216,870.00. Actual offer will be based on your qualifications. Pay Transparency Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat's compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience. About Red Hat Red Hat is the world's leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact. Benefits ● Comprehensive medical, dental, and vision coverage ● Flexible Spending Account - healthcare and dependent care ● Health Savings Account - high deductible medical plan ● Retirement 401(k) with employer match ● Paid time off and holidays ● Paid parental leave plans for all new parents ● Leave benefits including disability, paid family medical leave, and paid military leave ● Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more! Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States. Diversity, Equity & Inclusion at Red Hat Red Hat's culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from diverse backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions of diversity that compose our global village. Equal Opportunity Policy (EEO) Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law. Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email application-assistance@redhat.com. General inquiries, such as those regarding the status of a job application, will not receive a reply.

Apply share * link Copy link * email Email a friend info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Seattle, WA, USA; Mountain View, CA, USA; Bellevue, WA, USA. Minimum qualifications: * Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related field or equivalent practical experience. * 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree. * 3 years of experience in a data science role within a technology company. Preferred qualifications: * 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. About the job The Search, Real World Journeys team's mission is to inspire action by connecting people with experiences that make life better. We empower users to accomplish their goals by acquiring and generating valuable content and forging strong partnerships that benefit both users and partners. We are shaping the evolution of Google Search, ensuring it remains the world's leading source of information. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities * Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. * Implement custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent. * Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. * Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Separately format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Minimum qualifications: + Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related field or equivalent practical experience. + 5 years of experience in analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with an advanced degree. + Experience with consumer-facing technical products. Preferred qualifications: + PhD in statistics, economics, math, or a related quantitative field. At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. The Workspace Data Science team empowers product teams for Drive, Docs, Sheets, Slides, and Vids through development of key metrics, data-motivated insights, modeling, experimentation, and other forms of causal inference to grow product adoption and AI usage. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google (************************************* . + Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. + Use custom data infrastructure or existing data models as appropriate, using knowledge. Design and evaluate models to mathematically express and solve defined problems. + Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. + Own the process of gathering, extracting, and compiling data across sources via tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also ******************************* and ************************************************************* If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: ***************************************

info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Kirkland, WA, USA; Sunnyvale, CA, USA; New York, NY, USA. Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related field or equivalent practical experience. 5 years of experience in analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with an advanced degree. Experience with consumer-facing technical products. Preferred qualifications: PhD in statistics, economics, math, or a related quantitative field. About the job At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. The Workspace Data Science team empowers product teams for Drive, Docs, Sheets, Slides, and Vids through development of key metrics, data-motivated insights, modeling, experimentation, and other forms of causal inference to grow product adoption and AI usage. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. Use custom data infrastructure or existing data models as appropriate, using knowledge. Design and evaluate models to mathematically express and solve defined problems. Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. Own the process of gathering, extracting, and compiling data across sources via tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Apply share * link Copy link * email Email a friend info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Kirkland, WA, USA; Sunnyvale, CA, USA; New York, NY, USA. Minimum qualifications: * Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related field or equivalent practical experience. * 5 years of experience in analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with an advanced degree. * Experience with consumer-facing technical products. Preferred qualifications: * PhD in statistics, economics, math, or a related quantitative field. About the job At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. The Workspace Data Science team empowers product teams for Drive, Docs, Sheets, Slides, and Vids through development of key metrics, data-motivated insights, modeling, experimentation, and other forms of causal inference to grow product adoption and AI usage. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities * Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. * Use custom data infrastructure or existing data models as appropriate, using knowledge. Design and evaluate models to mathematically express and solve defined problems. * Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. * Own the process of gathering, extracting, and compiling data across sources via tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Apply share * link Copy link * email Email a friend info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Kirkland, WA, USA; Sunnyvale, CA, USA; New York, NY, USA. Minimum qualifications: * Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related field or equivalent practical experience. * 5 years of experience in analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with an advanced degree. * Experience with consumer-facing technical products. Preferred qualifications: * PhD in statistics, economics, math, or a related quantitative field. About the job At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. The Workspace Data Science team empowers product teams for Drive, Docs, Sheets, Slides, and Vids through development of key metrics, data-motivated insights, modeling, experimentation, and other forms of causal inference to grow product adoption and AI usage. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities * Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. * Use custom data infrastructure or existing data models as appropriate, using knowledge. Design and evaluate models to mathematically express and solve defined problems. * Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. * Own the process of gathering, extracting, and compiling data across sources via tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Seattle, WA, USA; Mountain View, CA, USA; Bellevue, WA, USA. Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related field or equivalent practical experience. 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree. 3 years of experience in a data science role within a technology company. Preferred qualifications: 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. About the job The Search, Real World Journeys team's mission is to inspire action by connecting people with experiences that make life better. We empower users to accomplish their goals by acquiring and generating valuable content and forging strong partnerships that benefit both users and partners. We are shaping the evolution of Google Search, ensuring it remains the world's leading source of information. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. Implement custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent. Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Separately format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Minimum qualifications: + Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related field or equivalent practical experience. + 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree. + 3 years of experience in a data science role within a technology company. Preferred qualifications: + 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. The Search, Real World Journeys team's mission is to inspire action by connecting people with experiences that make life better. We empower users to accomplish their goals by acquiring and generating valuable content and forging strong partnerships that benefit both users and partners. We are shaping the evolution of Google Search, ensuring it remains the world's leading source of information. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google (************************************* . + Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. + Implement custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent. + Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. + Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Separately format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also ******************************* and ************************************************************* If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: ***************************************