Data Scientist Jobs in Oakland, CA

Kindred is a members-only home swapping network that unlocks the ability to live a travel-rich lifestyle through the power of community. By exchanging primary residences with trusted peers, renters and owners alike can match with Kindred spirits and explore new destinations without breaking the bank. We are on a mission to build a sharing economy that lives up to the name, and we've raised significant capital from some of the best investors in Silicon Valley, including Index Ventures, Andreessen Horowitz, New Enterprise Associates, Bessemer Venture Partners, Caffeinated Capital, Elad Gil, and the founders of Opendoor, Figma, ClassPass, Clubhouse, Divvy, Gem, and Homebound. The co-founders are proven leaders from the early team at proptech company Opendoor ($15B+ exit) and have each separately built and scaled products that today do $1B+ annual revenue combined. We're looking for the world's top builders, executors, and believers to join us on this ride. You can learn more about us in Forbes and TechCrunch. The Role: This role offers an exceptional opportunity to shape the future of Kindred by directly influencing our core business strategy-from growth to operations. You will collaborate closely with a top-tier team of executives and engineers to tackle some of Kindred's most complex challenges, including optimizing the credit economy, balancing inventory, and refining dynamic pricing. We're looking for someone who thrives both as a hands-on individual contributor and leader, capable of diving deep into complex problems while building a world-class data science team. This role requires a rare combination of technical acumen, strategic foresight, and leadership excellence, with the potential to create a lasting, transformative impact on Kindred's success. Some of the challenges you will tackle include: Dispatch Priority: In a system without cash exchanges, Kindred requires an innovative “match” system to determine member booking priority based on factors such as home demand, similarity, and user reputation. Think of it similar to dispatch models for ride-sharing apps - ensuring the best possible matches while optimizing the member experience. Inventory Balance: Kindred's unique model, where every guest is also a host, means supply and demand are intrinsically linked - we cannot add a unit of supply without also adding a unit of demand. You will work closely with the marketing team to monitor and balance inventory, deploying various product and credit strategies to optimize the flywheel. Dynamic Pricing: You'll leverage market data to define and implement pricing strategies, ensuring Kindred delivers undeniable value to our members while meeting profitability targets. Intelligent Automation: You will lead the development and deployment of AI-driven solutions, such as an AI assisted concierge, to streamline customer support operations and enhance margins-while maintaining an exceptional, best-in-class member experience. You may be a right fit for this role if you: Have at least 10+ years of experience in data science, or a related field, with a strong background in leading complex, cross-functional projects and driving data-driven decision-making. MS / PhD in a quantitative discipline (e.g., Economics, Statistics, Machine learning) Demonstrate strategic foresight and are able to think beyond the immediate challenge. You can balance both short-term tactical priorities with long-term goals and strategically navigate competing demands. Have experience building and leading high-performing teams. You are capable of mentoring and growing a world-class data science team while working collaboratively with executives and other teams to drive company-wide impact. Are results-oriented and have a proven track record of delivering innovative, data-driven solutions that impact business performance, such as dynamic pricing models, inventory optimization, or customer segmentation. Have excellent communication skills and can clearly articulate complex data science concepts to non-technical stakeholders. You can effectively present insights, recommendations, and technical roadmaps to executives and other teams. Are customer-centric, with a deep understanding of how data science can enhance the user experience. You have a keen focus on delivering value to members while improving operational efficiency. Thrive in an entrepreneurial environment and are excited about the opportunity to build and scale solutions in fast-paced environment. Our Benefits: At Kindred, we know that good things happen when we look out for one another. We offer our employees the following benefits: Our opening spans more than one career level. The base salary offered depends on many factors, such as work experience, transferable skills, business needs and impact, and market demands. A vibrant, inclusive, and highly skilled team that ferociously protects team chemistry A culture of championship (vs. just mentorship), feedback, and continual development Competitive cash compensation and equity Comprehensive health benefits Flexible vacation policy Unlimited credits to stay at Kindred homes during your time as an employee $4,000 annual travel stipend to use toward travel costs to stay at a Kindred home Remote-flexible work environment. We encourage team members to travel and adventure, including working from Kindred HQ in San Francisco! Regular offsites to co-locate with the team

Business Integration Partners (BIP) is Europe's fastest growing digital consulting company and are on track to reach the Top 20 by 2025, with an expanding global footprint in the US (New York, Boston, Chicago, Tampa, Charlotte, Dallas, and Houston). Operating at the intersection of business and technology we design, develop, and deliver sustainable solutions at pace and scale creating greater value for our customers, employees, shareholders, and society. Position Overview: BIP US is seeking to grow its US consulting team and is looking for a Data Scientist with 5-7 years of experience to join our BIP Bay Area consulting team. This consultant will work at the intersection of Finance and Engineering, helping us optimize revenue, track key financial metrics, and improve decision-making with data-driven insights. This consultant must thrive in fast-paced environments, have a passion for digging into data to drive business strategy, and be able to bridge the gap between Finance and Engineering. You must have valid US work authorization and must physically reside in the Bay Area, within a 50-mile commute. We are unable to support relocation costs. Please do not apply for this position unless you meet the criteria outlined above. Key Responsibilities: Usage-Based Billing Analysis - Develop and refine billing models by product, ensuring alignment between revenue and usage data. Tracking Credits & Cost Margin Analysis - Monitor credit usage and analyze cost margins to optimize pricing strategies. Churn Modeling & Customer Retention - Build predictive models to identify risk factors for customer churn and develop strategies to improve retention. Agent Conversion Analytics - Analyze user behavior and engagement data to improve conversion rates from free to paid customers. Cycle Tracking & ARR Waterfall - Monitor customer lifecycle trends, track Annual Recurring Revenue (ARR) movements, and forecast financial outcomes. Cross-functional Collaboration - Work closely with Finance, Product, and Engineering teams to ensure data insights drive strategic business decisions. Qualifications: Bachelor's degree and 5-7 years of experience in Data Science, Analytics, or a related field. Strong expertise in data analytics, financial modeling, and business intelligence. Experience with programs & tools such as Hashboard, Amplitude, Stripe, Google, Apple, DBT Labs, Bitquery, and Python. Exceptional communication and storytelling skills - ability to present complex data in a clear and compelling way to executives. Strong problem-solving skills with a curious and proactive mindset -analyzing data, asking the right questions and finding solutions accordingly. Experience working cross-functionally with Finance (CFO/FP&A) and Engineering teams. Ability to thrive in ambiguity and adapt quickly in a high-growth startup environment. **The base salary range for this role is $150,000-$175,000** Benefits: Choice of medical, dental, vision insurance. Voluntary benefits. Short- and long-term disability. HSA and FSAs. Matching 401k. Discretionary performance bonus. Employee referral bonus. Employee assistance program. 9 public holidays. 22 days PTO. PTO buy and sell program. Volunteer days. Paid parental leave. Remote/hybrid work environment support. For more information about BIP US, visit ********************************* Equal Employment Opportunity: It is BIP US Consulting policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship, or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds. BIP US provides a reasonable range of compensation for our roles. Actual compensation is influenced by a wide array of factors including but not limited to skill set, education, level of experience, and knowledge.

Brahma Consulting Group is a Recruitment firm powered by a mission to deliver personalized, industry-focused recruitment solutions. We are currently assisting our client, a global leader in enterprise-grade data analytics and AI solutions, in their search for a Data Scientist in Mountain View, CA. This is a full-time permanent position. Responsibilities Analyze raw data: assessing quality, cleansing, structuring for downstream processing Design accurate and scalable prediction algorithms Collaborate with engineering team to bring analytical prototypes to production Generate actionable insights for business improvements Qualifications Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.) 3+ Years of Banking / Payments analytics experience preferably in a consulting set-up Strong experience of developing and deploying Predictive/ML solutions Proficiency in SQL, Tableau, Python Strong experience in Big Data Technologies like Hadoop, Spark or similar platforms Excellent communication skills and strong stakeholder management experience Strong problem-solving skills Proficiency in Mandarin is a plus

About Us: LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 700+ clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree - a Larsen & Toubro Group company - combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. For more information, please visit ******************** Job Title: Senior Data Scientist Location: San Jose, California Duration: Fulltime Job Summary: Key Responsibilities: We are looking for an experienced Senior Data Scientist with 10 to 12 years of experience in data science specializing in machine learning python statistical modelling and big data technologiespyspark sql The ideal candidate will have a strong background in developing and deploying machine learning models optimizing ML pipelines and handling largescale structured and unstructured data to drive business impact Deep understanding of supervised and unsupervised learning including regression classification Multiclass classification clustering and NLP Proficiency in statistical analysis AB testing and causal inference techniques Experience with model deployment and MLOps in cloud environments AWS GCP Key Responsibilities Develop and deploy machine learning models and predictive analytics solutions for business impact Work with largescale structured and unstructured data to extract insights and build scalable models Design implement and optimize ML pipelines for realtime and batch processing Collaborate with engineering product and business stakeholders to translate business problems into data science solutions Apply statistical modeling AB testing and causal inference techniques to evaluate business performance Apply machine learning and statistical techniques for audience segmentation helping to identify patterns and optimise business strategies Drive research and innovation by staying updated with cuttingedge MLAI advancements and incorporating them into our solutions Optimize data science models for performance scalability and interpretability in production environments Mentor junior data scientists and contribute to best practices in data science and engineering Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”): Benefits and Perks: Comprehensive Medical Plan Covering Medical, Dental, Vision Short Term and Long-Term Disability Coverage 401(k) Plan with Company match Life Insurance Vacation Time, Sick Leave, Paid Holidays Paid Paternity and Maternity Leave The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay and other forms of bonus or variable compensation. Disclaimer: The compensation and benefits information provided herein is accurate as of the date of this posting. LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law. Safe return to office: In order to comply with LTIMindtree' s company COVID-19 vaccine mandate, candidates must be able to provide proof of full vaccination against COVID-19 before or by the date of hire. Alternatively, one may submit a request for reasonable accommodation from LTIMindtree's COVID-19 vaccination mandate for approval, in accordance with applicable state and federal law, by the date of hire. Any request is subject to review through LTIMindtree's applicable processes.

We are seeking an experienced Senior Data Scientist with over 5 years of experience in Data Science, Machine Learning (ML), and Artificial Intelligence (AI) to join our team in Redwood City, SF Bay Area. Key Responsibilities: Architect and design scalable and enterprise-level AI/ML models to solve complex business challenges. Develop and optimize AI/ML algorithms to ensure high performance, accuracy, and efficiency. Lead the end-to-end AI/ML lifecycle, including data collection, preprocessing, modeling, deployment, monitoring, and maintenance. Collaborate with software engineers, data engineers, and product managers to integrate AI solutions seamlessly into existing systems. Stay ahead of industry trends, exploring and implementing the latest advancements in AI, ML, deep learning, and data science. Ensure best practices in ML model validation, interpretability, and performance optimization. Mentor and guide junior data scientists and ML engineers, fostering a culture of innovation and technical excellence. Work with big data technologies and cloud platforms such as AWS, GCP, or Azure to scale AI/ML solutions. Implement MLOps practices to streamline deployment, monitoring, and retraining of ML models in production. Required Qualifications: 5+ years of experience in Data Science, Machine Learning, or AI with a strong track record of delivering impactful AI solutions. Expert-level proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn. Deep expertise in machine learning algorithms, deep learning, NLP, computer vision, and reinforcement learning. Proven experience in AI/ML model architecture, optimization techniques, and deploying models at scale. Strong knowledge of data engineering principles, including data pipelines, feature engineering, and ETL processes. Hands-on experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Hadoop, Snowflake). Strong background in statistics, mathematics, and probability theory. Experience with MLOps, model deployment, and monitoring in production environments. Excellent problem-solving skills, critical thinking, and adaptability in a fast-paced environment. Strong communication skills, with the ability to present complex AI concepts to non-technical stakeholders. Preferred Qualifications: Bachelors or Masters in Computer Science. Experience with real-time AI applications. Knowledge of AI ethics, explainability, and responsible AI frameworks. Why Join Us? Cutting-edge AI/ML projects: Work on innovative solutions with real-world impact across industries. Collaborative and high-growth environment: Work alongside top talent in AI, data science, and engineering. Competitive compensation & benefits: Market-leading salary, stock options, and career growth opportunities.

Job Title: Senior Data Scientist (MarTech) Duration: 12+ months Contract (Potential to extend) Pay: $100/$110/Hr on W2 (depends upon experience) MarTech Data Science Measurement empowers Client to optimize marketing ROI by generating data-driven recommendations. We lead the way in defining and advancing best practices for measuring and optimizing marketing impact. We collaborate with Marketing, Finance, and Engineering to provide actionable recommendations and tools based on effective, timely, and granular measurements. Our team's tenets are: Actionable: Deliver insights that drive confident business decisions. Impactful: Prioritize projects based on their expected value to Client. Balanced: Adapt methods to business questions and data realities, acknowledging limitations. Rigorous: Maintain methodological integrity and quantify the sensitivity of findings. Innovative: Invest in advancing measurement science and developing new methods. Influential: Share learnings across Client and the broader data science community. The difference you will make: We are seeking an experienced Data Scientist with deep expertise and experience building data pipelines and automating measurement systems. The ideal candidate will have experience working with Apache Airflow and Spark, as well as a comprehensive understanding of SQL. They are expected to be fluent in multiple statistical programming languages, particularly R and Python. They should also be familiar with causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts. A typical day: Data Pipelines: Build novel data pipelines that accelerate the work of our data science team, including automating data validation, unit testing, and other common processes. Productionalizing Prototypes: Refine prototypes built by other scientists and prepare them to be productionalized within Client's systems. Causal Inference: Apply and develop causal inference methods, especially around MMM, to estimate the effectiveness of Client's marketing initiatives. Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts. Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies. Your expertise: PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience. Deep knowledge of data management tools, systems, and processes, including Apache Airflow and Spark. Proficiency in statistical programming (Python and R) and database usage (SQL). Experience with media mix modeling (MMM). Ability to communicate complex concepts clearly to stakeholders at varying technical levels. Proven track record of solving business problems through data science methods. Preferred expertise: Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field. Familiarity with Bayesian modeling and its applications in marketing. Experience with causal ML modeling. Experience in developing end-to-end models for data-driven decision-making.

This is a senior position that requires existing and deep hands-on experience. This is an Applied, Data Science Engineering role: you need to be a data scientist first, with all the deep theoretical foundations to be able to design, build, train, and hypertune ML/DL models, and at the same time have all the practical, hands on, engineering know-how to be able to deploy the models in scalable production environment. DO NOT apply if you are a: recent graduate: this is not your first job. data scientist but haven't been part of deploying your models in real world, production environment. data engineer but haven't designed multimodal models and don't know the inner-workings of ML/DL algos. Our interviews include in-person, face-to-face sessions: do not apply if you can't meet in person, or are unable to take interviews without the help of an AI chatbot. NO RECRUITERS PLEASE. Cognomotiv's Market The complexity of modern vehicles is increasing at breakneck speed. The introduction of an array of brand-new features, along with refinements on old capabilities, has wildly expanded the role of AI, software, and in-vehicle services in today's vehicles. More and more functionality is shifting from electronic and mechanical systems to onboard computers controlled by AI. This trend is only accelerating: myriad of new services rely heavily on vehicles being constantly online, while autonomy is becoming increasingly real. AI and software services offer amazing new opportunities to the automotive world, but bring with them complexity that creates maintenance and repair challenges and operational failures due to underlying hardware, software, and AI that control them. Who We Are At Cognomotiv, we help automotive OEMs, Fleet Operators, suppliers, and service centers guarantee the reliability of every vehicle on the road, thanks to state-of-the-art AI that identifies anomalous vehicle behavior in real time, detect and predict issues, and provide guidance on how to fix the problems. The Cognomotiv solution is a blend of edge and backend AI that performs non-intrusive system diagnosis and prognosis, and makes remediation recommendations with powerful and efficient native models. Our AI is unique in its ability to perform fault and failure detection and prediction in both resource constrained environment as in the edge, as well as in the cloud, and also provide guided repair. Cognomotiv is the ultimate professional grade MRO (Maintenance, Repair, Overhaul) Copilot. Description We are seeking an ambitious, self-reliant data science engineer who operates with a sense of urgency and has the ability to thrive in a fast-paced environment. You will design and build the robust, supportable, highly scalable AI foundation of Cognomotiv's solution: ● Optimize and test ML and statistical models to report and predict systems' health in a variety of subsystems, including mechanical, sensor, and onboard computer. ● Research and develop methods for anomaly detection, failure diagnosis, and root cause analysis using systems data streams as well as information about the system. ● Design and implement models to detect breaches in system reliability. ● Organize and manage fleet data flow, storage, and automated procedures. ● Use variety of ML/DL techniques to mine data for fault patterns and precursors. ● Build and deploy RAG, Generative and Agentic AI to automate scalable guided-repair procedure generation. ● Organize and clearly present or publish findings. ● Assist in porting models to native language for edge computation and learning. You possess deep technical skills that will be used to drive insights into new products, working closely with both data scientists and engineers. You will have the opportunity to synthesize learning from edge-trained models, a paradigm the entire IoT is striving for. You will have access to new and rich datasets, and use it to directly provide safety and reliability to all fully- or semi-automated systems. Education & Experience Requirements: ● Degree (advanced preferred, Ph.D., or equivalent experience) in a quantitative field such as statistics or physics ● 5+ years of industry experience in a data science engineering role ● Proficiency in large scale data interaction -- SQL, Hadoop, etc. ● Existing experience in the designing, building, and deploying multimodal ML/DL a huge plus ● Existing experience in working with both streaming and batch mode ML/DL a huge plus ● Expert knowledge of one more more scripting languages (e.g. Python) ● Basic proficiency in at least one object-oriented programming language (e.g. C++, Java) ● Solid understanding and working knowledge of RAG, SLM, Graphs, GNN, Agentic AI ● Solid understanding and working knowledge of fundamental probability and statistics ● Effective communication skills: can turn vague, startup-grade input to concrete, value-added output ● The ideal candidate can independently recognize needs/possibilities and provide creative solutions.

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. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. 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 1 billion 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 seeking a talented and driven individual to accelerate our efforts and contribute to LinkedIn's data-centric culture. In this role, you will tackle a wide range of technical challenges spanning products, engineering, research, data engineering, finance, and infrastructure. Leveraging data and analysis, you will address critical challenges within our infrastructure organization, shaping product strategy and guiding investment decisions with data-driven insights. LinkedIn's infrastructure is the backbone of our operations, encompassing datacenters, servers, network infrastructure, power systems, and foundational software platforms that power our products and services. 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. • Develop methodologies to enhance LinkedIn's operations and platform capabilities. • Apply technical expertise to our forecasting and capacity planning process to seek opportunities of improvement • 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. • 5+ 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: • 7+ years of industry or relevant academia experience • MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc. or other quantitative field. • Experience in infrastructure planning, operations research, or a related field • Familiarity with cloud computing platforms and infrastructure management systems. Suggested Skills • Statistical Modeling • Forecasting • Programming • Data Analysis • Infrastructure Planning 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 $164,000 - $268,000. 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: ***************************************

$165,000 - $185,000 BASE SALARY + EQUITY REMOTE OR HYBRID (3 DAYS ONSITE IF LOCAL) A fast-growing healthtech startup developing solutions to help healthcare organizations safely implement generative AI. Their platform ensures compliance, enhances model reliability, and provides ongoing monitoring to support responsible AI adoption. THE ROLE As a Data Engineer, you will design and optimize scalable ETL pipelines, standardize data processing workflows, and integrate healthcare data across various platforms. You'll play a key role in automating data ingestion, enhancing system reliability, and ensuring high-quality datasets for AI applications. This position requires problem-solving ability, adaptability, and a strong interest in the intersection of healthcare and AI. ROLE RESPONSIBILITIES Develop and maintain ETL pipelines that extract data from FHIR endpoints. Build and enhance data ingestion processes to streamline healthcare system integration. Automate data workflows for seamless interaction with Epic and other EHR platforms. Establish repeatable data transformation patterns to ensure consistency across systems. Deploy Infrastructure-as-Code (IaC) solutions for efficient scaling. Work closely with AI/ML teams to provide clean, structured data for model development. SKILLS & EXPERIENCE 4+ years of experience working with healthcare datasets. Strong programming skills in Python. Hands-on experience with FHIR & HL7v2 data standards. Cloud expertise in Azure (preferred), GCP, or AWS. Experience working with Snowflake & Databricks is a plus. Proven ability to scale ETL pipelines in live production environments. Familiarity with Infrastructure-as-Code (IaC) and CI/CD pipelines. Exposure to AI/ML data engineering is a plus, particularly in model training workflows. BENEFITS $165,000 - $185,000 base salary + equity. Flexible remote or hybrid work model. Opportunity to shape the future of AI governance in healthcare. If you're a data engineer passionate about AI in healthcare, we'd love to connect!

***Hybrid Data Engineer consulting opportunity in San Francisco, CA**** Focus on SQL Knowledge and workflow management (airflow tool) and Machine Learning Knowledge: Specifically Feature. Understanding data inputs into the model and feature analysis. Feature Engineering. Training data set composition. Experience with Pyspark to perform data transformations, feature engineering, data analysis, and ML training data generation. This role supports the feature generation, data workflows, and maintenance of the RealTIME personalization models for the Campaigns fleet. ***Streaming industry experience is a huge plus!*** EXTERNAL JOB DESCRIPTION: Department Overview: Applied Machine Learning Engineers, Data Engineers, and Data Scientists on the Disney Streaming Machine Learning and Innovation team develop and maintain recommendation and personalization algorithms for Streaming's suite of streaming video apps. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes. Our team is… • A group of engineers and data scientists with diverse expertise delivering solutions together. • Collaborative and dynamic. • Embracing agile practices. • Using continuous integration/automated testing. • Led by startup veterans. Basic Qualifications Required Qualifications: ● 2+ years of data engineering experience ● Deep knowledge of the Python data ecosystem ● Great coding and problem-solving skills ● Experience in building large datasets and scalable services ● Experience deploying and running services in AWS and in engineering big-data solutions using technologies like Databricks, EMR, S3, Spark, and Docker ● Experience with Pyspark to perform data transformations, feature engineering, data analysis, and ML training data generation ● Excellent communication and people engagement skills Preferred Qualifications ● Experience building streaming pipelines using Kafka, Spark, or Flink ● ML algorithmic and systems knowledge/experience Responsibilities: ● Partner with technical and non-technical colleagues to understand ML algorithm feature, data, and workflow requirements. ● Implement necessary feature analysis, new features, training datasets and related workflows and monitoring metrics and services ● Work with Engineering teams to collect required data from internal and external systems ● Develop and maintain ETL routines using orchestration tools such as Airflow ● Collaborate with machine learning practitioners to design and build model and data forward solutions ● Deploy scalable streaming and batch data pipelines to support petabyte scale datasets ● Enforce common data design patterns to increase code maintainability ● Create ETL architecture designs and conduct reviews ● Perform ad hoc data analysis and maintenance as necessary ● Partner with team leads to identify, design, and implement internal process improvements ● Drive and maintain a culture of quality, innovation, and experimentation ● Work in an Agile environment that focuses on collaboration and teamwork Required Education Bachelor's degree or relevant years of work experience

Hi, Job Title: Senior Data Engineer Duration: Contract to Hire Role Interview Process: Onsite Payrate: 75 to 80/hr. on C2C Responsibilities: Key Responsibilities: Design, develop, and maintain data pipelines using Spark, PySpark, and other big data technologies to process large datasets. Build and optimize complex SQL queries for data extraction, transformation, and loading (ETL) in both batch and real-time workflows. Work with cloud platforms such as AWS, Azure, or GCP to deploy and manage data infrastructure. Collaborate with cross-functional teams to gather data requirements and deliver data solutions that meet business needs. Ensure data quality, integrity, and consistency across different stages of data processing. Optimize and troubleshoot performance of Spark and SQL-based applications. Develop and implement data models and data architectures to support analytics and business intelligence initiatives. Create and maintain automated data workflows and ensure they are scalable and maintainable. Document data processes, architectures, and pipelines to ensure knowledge sharing across teams. Required Skills & Qualifications: Proven experience as a Data Engineer with expertise in Spark and PySpark for distributed data processing. Strong proficiency in SQL, including experience with writing complex queries, performance tuning, and database management. Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their data processing services such as AWS EMR, Azure Databricks, Google BigQuery, etc. In-depth understanding of ETL processes, data modelling, and data warehousing concepts. Experience working with large datasets and optimizing data pipelines for efficiency and scalability. Familiarity with data storage technologies like Hadoop, HDFS, and cloud-based data lakes. Knowledge of version control systems like Git, and experience working in Agile environments. Excellent problem-solving skills and the ability to work in a fast-paced, collaborative team environment. Strong communication skills and the ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications: Experience with containerization and orchestration tools like Docker, Kubernetes, or Apache Airflow. Familiarity with machine learning concepts and integration of data pipelines with ML workflows. Experience with real-time data streaming technologies (Kafka, Apache Flink, etc.). Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.

Calling All Data Engineers! Join a groundbreaking fintech revolution! We're seeking a BI/Data Engineer to be part of a Global Engineering Team building the future of blockchain payments. Our client has developed a cutting-edge blockchain payment platform, reshaping traditional payment systems and driving the mobile fintech revolution. Are you the type of engineer who thinks, "If I could rebuild this entire system, here's how I'd do it right"? If so, this role is for you. What You'll Do: ✅ Build and operate an Analytics Platform using AWS Native services to process streamed data across a blockchain-based payment network. ✅ Organize incoming data into structured formats for querying, reporting, and system feedback. ✅ Collaborate with product teams to implement fraud detection algorithms that enhance system security. ✅ Provide analytics for blockchain payment transaction performance management. ✅ Transform unstructured data into structured formats, optimizing data streams at their source. ✅ Design dashboards and query interfaces for operational data. ✅ Optimize data transmission by filtering out unnecessary sources. What You Bring: ✔ 2-3 years of experience with Elastic, Logstash, Kibana. ✔ Hands-on experience working with unstructured and semi-structured data. ✔ Background in fraud detection, risk analysis, and payments. ✔ Startup experience - you thrive in a fast-paced, high-growth environment. Why Join? 🚀 Be an early engineer in a small company with a big vision. 📈 Opportunities to grow a team and shape industry-leading systems. 🏡 Hybrid workspace in Silicon Valley with a competitive benefits package. 🔥 Work with driven innovators who love the startup grind! Sound like you? Reach out to **************************

Business Integration Partners (BIP) is Europe's fastest growing digital consulting company and are on track to reach the Top 20 by 2025, with an expanding global footprint in the US (New York, Boston, Chicago, Tampa, Charlotte, Dallas, and Houston). Operating at the intersection of business and technology we design, develop, and deliver sustainable solutions at pace and scale creating greater value for our customers, employees, shareholders, and society. Position Overview: BIP US is seeking to grow its US consulting team and is looking for a Data Scientist with 5-7 years of experience to join our BIP Bay Area consulting team. This consultant will work at the intersection of Finance and Engineering, helping us optimize revenue, track key financial metrics, and improve decision-making with data-driven insights. This consultant must thrive in fast-paced environments, have a passion for digging into data to drive business strategy, and be able to bridge the gap between Finance and Engineering. You must have valid US work authorization and must physically reside in the Bay Area, within a 50-mile commute. We are unable to support relocation costs. Please do not apply for this position unless you meet the criteria outlined above. Key Responsibilities: Usage-Based Billing Analysis - Develop and refine billing models by product, ensuring alignment between revenue and usage data. Tracking Credits & Cost Margin Analysis - Monitor credit usage and analyze cost margins to optimize pricing strategies. Churn Modeling & Customer Retention - Build predictive models to identify risk factors for customer churn and develop strategies to improve retention. Agent Conversion Analytics - Analyze user behavior and engagement data to improve conversion rates from free to paid customers. Cycle Tracking & ARR Waterfall - Monitor customer lifecycle trends, track Annual Recurring Revenue (ARR) movements, and forecast financial outcomes. Cross-functional Collaboration - Work closely with Finance, Product, and Engineering teams to ensure data insights drive strategic business decisions. Qualifications: Bachelor's degree and 5-7 years of experience in Data Science, Analytics, or a related field. Strong expertise in data analytics, financial modeling, and business intelligence. Experience with programs & tools such as Hashboard, Amplitude, Stripe, Google, Apple, DBT Labs, Bitquery, and Python. Exceptional communication and storytelling skills - ability to present complex data in a clear and compelling way to executives. Strong problem-solving skills with a curious and proactive mindset -analyzing data, asking the right questions and finding solutions accordingly. Experience working cross-functionally with Finance (CFO/FP&A) and Engineering teams. Ability to thrive in ambiguity and adapt quickly in a high-growth startup environment. **The base salary range for this role is $150,000-$175,000** Benefits: Choice of medical, dental, vision insurance. Voluntary benefits. Short- and long-term disability. HSA and FSAs. Matching 401k. Discretionary performance bonus. Employee referral bonus. Employee assistance program. 9 public holidays. 22 days PTO. PTO buy and sell program. Volunteer days. Paid parental leave. Remote/hybrid work environment support. For more information about BIP US, visit ********************************* Equal Employment Opportunity: It is BIP US Consulting policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship, or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds. BIP US provides a reasonable range of compensation for our roles. Actual compensation is influenced by a wide array of factors including but not limited to skill set, education, level of experience, and knowledge.

We are seeking an experienced Senior Data Scientist with over 5 years of experience in Data Science, Machine Learning (ML), and Artificial Intelligence (AI) to join our team in Redwood City, SF Bay Area. Key Responsibilities: Architect and design scalable and enterprise-level AI/ML models to solve complex business challenges. Develop and optimize AI/ML algorithms to ensure high performance, accuracy, and efficiency. Lead the end-to-end AI/ML lifecycle, including data collection, preprocessing, modeling, deployment, monitoring, and maintenance. Collaborate with software engineers, data engineers, and product managers to integrate AI solutions seamlessly into existing systems. Stay ahead of industry trends, exploring and implementing the latest advancements in AI, ML, deep learning, and data science. Ensure best practices in ML model validation, interpretability, and performance optimization. Mentor and guide junior data scientists and ML engineers, fostering a culture of innovation and technical excellence. Work with big data technologies and cloud platforms such as AWS, GCP, or Azure to scale AI/ML solutions. Implement MLOps practices to streamline deployment, monitoring, and retraining of ML models in production. Required Qualifications: 5+ years of experience in Data Science, Machine Learning, or AI with a strong track record of delivering impactful AI solutions. Expert-level proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn. Deep expertise in machine learning algorithms, deep learning, NLP, computer vision, and reinforcement learning. Proven experience in AI/ML model architecture, optimization techniques, and deploying models at scale. Strong knowledge of data engineering principles, including data pipelines, feature engineering, and ETL processes. Hands-on experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Hadoop, Snowflake). Strong background in statistics, mathematics, and probability theory. Experience with MLOps, model deployment, and monitoring in production environments. Excellent problem-solving skills, critical thinking, and adaptability in a fast-paced environment. Strong communication skills, with the ability to present complex AI concepts to non-technical stakeholders. Preferred Qualifications: Bachelors or Masters in Computer Science. Experience with real-time AI applications. Knowledge of AI ethics, explainability, and responsible AI frameworks. Why Join Us? Cutting-edge AI/ML projects: Work on innovative solutions with real-world impact across industries. Collaborative and high-growth environment: Work alongside top talent in AI, data science, and engineering. Competitive compensation & benefits: Market-leading salary, stock options, and career growth opportunities.

Job Title: Senior Data Scientist (MarTech) Duration: 12+ months Contract (Potential to extend) Pay: $100/$110/Hr on W2 (depends upon experience) MarTech Data Science Measurement empowers Client to optimize marketing ROI by generating data-driven recommendations. We lead the way in defining and advancing best practices for measuring and optimizing marketing impact. We collaborate with Marketing, Finance, and Engineering to provide actionable recommendations and tools based on effective, timely, and granular measurements. Our team's tenets are: Actionable: Deliver insights that drive confident business decisions. Impactful: Prioritize projects based on their expected value to Client. Balanced: Adapt methods to business questions and data realities, acknowledging limitations. Rigorous: Maintain methodological integrity and quantify the sensitivity of findings. Innovative: Invest in advancing measurement science and developing new methods. Influential: Share learnings across Client and the broader data science community. The difference you will make: We are seeking an experienced Data Scientist with deep expertise and experience building data pipelines and automating measurement systems. The ideal candidate will have experience working with Apache Airflow and Spark, as well as a comprehensive understanding of SQL. They are expected to be fluent in multiple statistical programming languages, particularly R and Python. They should also be familiar with causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts. A typical day: Data Pipelines: Build novel data pipelines that accelerate the work of our data science team, including automating data validation, unit testing, and other common processes. Productionalizing Prototypes: Refine prototypes built by other scientists and prepare them to be productionalized within Client's systems. Causal Inference: Apply and develop causal inference methods, especially around MMM, to estimate the effectiveness of Client's marketing initiatives. Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts. Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies. Your expertise: PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience. Deep knowledge of data management tools, systems, and processes, including Apache Airflow and Spark. Proficiency in statistical programming (Python and R) and database usage (SQL). Experience with media mix modeling (MMM). Ability to communicate complex concepts clearly to stakeholders at varying technical levels. Proven track record of solving business problems through data science methods. Preferred expertise: Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field. Familiarity with Bayesian modeling and its applications in marketing. Experience with causal ML modeling. Experience in developing end-to-end models for data-driven decision-making.

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. 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 1 billion 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. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. 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 $134,000 to $221,000 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: ***************************************

$165,000 - $185,000 BASE SALARY + EQUITY REMOTE OR HYBRID (3 DAYS ONSITE IF LOCAL) A fast-growing healthtech startup developing solutions to help healthcare organizations safely implement generative AI. Their platform ensures compliance, enhances model reliability, and provides ongoing monitoring to support responsible AI adoption. THE ROLE As a Data Engineer, you will design and optimize scalable ETL pipelines, standardize data processing workflows, and integrate healthcare data across various platforms. You'll play a key role in automating data ingestion, enhancing system reliability, and ensuring high-quality datasets for AI applications. This position requires problem-solving ability, adaptability, and a strong interest in the intersection of healthcare and AI. ROLE RESPONSIBILITIES Develop and maintain ETL pipelines that extract data from FHIR endpoints. Build and enhance data ingestion processes to streamline healthcare system integration. Automate data workflows for seamless interaction with Epic and other EHR platforms. Establish repeatable data transformation patterns to ensure consistency across systems. Deploy Infrastructure-as-Code (IaC) solutions for efficient scaling. Work closely with AI/ML teams to provide clean, structured data for model development. SKILLS & EXPERIENCE 4+ years of experience working with healthcare datasets. Strong programming skills in Python. Hands-on experience with FHIR & HL7v2 data standards. Cloud expertise in Azure (preferred), GCP, or AWS. Experience working with Snowflake & Databricks is a plus. Proven ability to scale ETL pipelines in live production environments. Familiarity with Infrastructure-as-Code (IaC) and CI/CD pipelines. Exposure to AI/ML data engineering is a plus, particularly in model training workflows. BENEFITS $165,000 - $185,000 base salary + equity. Flexible remote or hybrid work model. Opportunity to shape the future of AI governance in healthcare. If you're a data engineer passionate about AI in healthcare, we'd love to connect!

Business Integration Partners (BIP) is Europe's fastest growing digital consulting company and are on track to reach the Top 20 by 2025, with an expanding global footprint in the US (New York, Boston, Chicago, Tampa, Charlotte, Dallas, and Houston). Operating at the intersection of business and technology we design, develop, and deliver sustainable solutions at pace and scale creating greater value for our customers, employees, shareholders, and society. Position Overview: BIP US is seeking to grow its US consulting team and is looking for a Data Scientist with 5-7 years of experience to join our BIP Bay Area consulting team. This consultant will work at the intersection of Finance and Engineering, helping us optimize revenue, track key financial metrics, and improve decision-making with data-driven insights. This consultant must thrive in fast-paced environments, have a passion for digging into data to drive business strategy, and be able to bridge the gap between Finance and Engineering. You must have valid US work authorization and must physically reside in the Bay Area, within a 50-mile commute. We are unable to support relocation costs. Please do not apply for this position unless you meet the criteria outlined above. Key Responsibilities: Usage-Based Billing Analysis - Develop and refine billing models by product, ensuring alignment between revenue and usage data. Tracking Credits & Cost Margin Analysis - Monitor credit usage and analyze cost margins to optimize pricing strategies. Churn Modeling & Customer Retention - Build predictive models to identify risk factors for customer churn and develop strategies to improve retention. Agent Conversion Analytics - Analyze user behavior and engagement data to improve conversion rates from free to paid customers. Cycle Tracking & ARR Waterfall - Monitor customer lifecycle trends, track Annual Recurring Revenue (ARR) movements, and forecast financial outcomes. Cross-functional Collaboration - Work closely with Finance, Product, and Engineering teams to ensure data insights drive strategic business decisions. Qualifications: Bachelor's degree and 5-7 years of experience in Data Science, Analytics, or a related field. Strong expertise in data analytics, financial modeling, and business intelligence. Experience with programs & tools such as Hashboard, Amplitude, Stripe, Google, Apple, DBT Labs, Bitquery, and Python. Exceptional communication and storytelling skills - ability to present complex data in a clear and compelling way to executives. Strong problem-solving skills with a curious and proactive mindset -analyzing data, asking the right questions and finding solutions accordingly. Experience working cross-functionally with Finance (CFO/FP&A) and Engineering teams. Ability to thrive in ambiguity and adapt quickly in a high-growth startup environment. **The base salary range for this role is $150,000-$175,000** Benefits: Choice of medical, dental, vision insurance. Voluntary benefits. Short- and long-term disability. HSA and FSAs. Matching 401k. Discretionary performance bonus. Employee referral bonus. Employee assistance program. 9 public holidays. 22 days PTO. PTO buy and sell program. Volunteer days. Paid parental leave. Remote/hybrid work environment support. For more information about BIP US, visit ********************************* Equal Employment Opportunity: It is BIP US Consulting policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship, or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds. BIP US provides a reasonable range of compensation for our roles. Actual compensation is influenced by a wide array of factors including but not limited to skill set, education, level of experience, and knowledge.

We are seeking an experienced Senior Data Scientist with over 5 years of experience in Data Science, Machine Learning (ML), and Artificial Intelligence (AI) to join our team in Redwood City, SF Bay Area. Key Responsibilities: Architect and design scalable and enterprise-level AI/ML models to solve complex business challenges. Develop and optimize AI/ML algorithms to ensure high performance, accuracy, and efficiency. Lead the end-to-end AI/ML lifecycle, including data collection, preprocessing, modeling, deployment, monitoring, and maintenance. Collaborate with software engineers, data engineers, and product managers to integrate AI solutions seamlessly into existing systems. Stay ahead of industry trends, exploring and implementing the latest advancements in AI, ML, deep learning, and data science. Ensure best practices in ML model validation, interpretability, and performance optimization. Mentor and guide junior data scientists and ML engineers, fostering a culture of innovation and technical excellence. Work with big data technologies and cloud platforms such as AWS, GCP, or Azure to scale AI/ML solutions. Implement MLOps practices to streamline deployment, monitoring, and retraining of ML models in production. Required Qualifications: 5+ years of experience in Data Science, Machine Learning, or AI with a strong track record of delivering impactful AI solutions. Expert-level proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn. Deep expertise in machine learning algorithms, deep learning, NLP, computer vision, and reinforcement learning. Proven experience in AI/ML model architecture, optimization techniques, and deploying models at scale. Strong knowledge of data engineering principles, including data pipelines, feature engineering, and ETL processes. Hands-on experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Hadoop, Snowflake). Strong background in statistics, mathematics, and probability theory. Experience with MLOps, model deployment, and monitoring in production environments. Excellent problem-solving skills, critical thinking, and adaptability in a fast-paced environment. Strong communication skills, with the ability to present complex AI concepts to non-technical stakeholders. Preferred Qualifications: Bachelors or Masters in Computer Science. Experience with real-time AI applications. Knowledge of AI ethics, explainability, and responsible AI frameworks. Why Join Us? Cutting-edge AI/ML projects: Work on innovative solutions with real-world impact across industries. Collaborative and high-growth environment: Work alongside top talent in AI, data science, and engineering. Competitive compensation & benefits: Market-leading salary, stock options, and career growth opportunities.