Data Scientist Jobs in Bakersfield, CA

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

Job Title: Full Stack Data Scientist & Engineer About Confidential/Stealth Asset Manager: Our client is a is a global investment firm, based in Menlo Park, with a mission to achieve the multi-generational goals and aspirations of our clients. Rooted in the endowment style of investing, we seek balanced diversification in order to protect and grow multi-generational capital over the long term. We are committed to the highest professional standards as fiduciaries of our clients' capital and our firm. We are a collaborative and innovative team that thrives in a fast-paced environment and is committed to generating superior returns for our clients. We value intellectual curiosity, creative thinking, and a passion for using data to drive investment decisions. We foster a culture of mentorship and collaboration, providing opportunities for professional growth and development. We are looking for a full-stack Data Engineer/Scientist. The role involves maintaining and extending scalable data warehouses and data lakes, designing robust data pipelines, and building dashboards and applications to visualize and analyze data However, there will be opportunities to take on expanded roles depending on the firm's needs, personal interest and ability to take on more responsibilities: We're looking for someone who: Has strong problem-solving skills and is an independent thinker Displays excellent communication and interpersonal skills, especially with their internal customers Takes initiative and a high degree of ownership and pride in their work Connects with the high-level goals and can work independently Is curious about new technologies and the investment industry Seeks to understand the broader business (e.g., the clients, their problems, the opportunities) Responsibilities: Maintain and extend scalable data warehouses and data lakes to support business intelligence and analytics Design, develop, and implement robust data pipelines to collect, transform, and store data from various sources Provide operational support for our cloud infrastructure Build dashboards and applications to visualize and analyze data Constructing quantitative investment tools Support other analysts in their use of data and analytical tools Document data pipelines and processes for knowledge sharing Stay up-to-date on the latest data engineering and data science technologies Project planning and project leadership Experience: 4-6 years of experience in a data engineering or data science role Demonstrated ability to independently lead and complete data-driven projects Experience with the full data engineering and data science stack, including: Cloud administration and DevOps practices Data warehousing and data lakehouse architectures and platforms (e.g., Databricks, Snowflake) ETL tools and techniques (e.g., Airflow, dbt) Programming languages (Python, SQL) Designing and building analytical applications Data visualization tools (e.g., Power BI, Sigma) Machine learning libraries (e.g., Scikit-learn) Compensation: Competitive compensation, bonus and benefits package including health, life insurance, backup childcare coverage, and 401k benefits.

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.

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.

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.

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 causal analysis and develop causal methodology and machine learning models 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. • 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. 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 $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. 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Responsibilities: 1.Design and Build Data Pipelines: •Develop, construct, test, and maintain data pipelines to extract, transform, and load (ETL) data from various sources to data warehouses or data lakes. •Ensure data pipelines are efficient, scalable, and maintainable, enabling seamless data flow for downstream analysis and modeling. •Work with stakeholders to identify data requirements and implement effective data processing solutions. 2. Data Integration: •Integrate data from multiple sources such as internal databases, external APIs, third-party vendors, and flat files. •Collaborate with business teams to understand data needs and ensure data is structured properly for reporting and analytics. •Build and optimize data ingestion systems to handle both real-time and batch data processing. 3. Data Storage and Management: •Design and manage data storage solutions (e.g., relational databases, NoSQL databases, data lakes, cloud storage) that support large-scale data processing. •Implement best practices for data security, backup, and disaster recovery, ensuring that data is safe, recoverable, and complies with relevant regulations. •Manage and optimize storage systems for scalability and cost efficiency. 4. Data Transformation: •Develop data transformation logic to clean, enrich, and standardize raw data, ensuring it is suitable for analysis. •Implement data transformation frameworks and tools, ensuring they work seamlessly across different data formats and sources. •Ensure the accuracy and integrity of data as it is processed and stored. 5. Automation and Optimization: •Automate repetitive tasks such as data extraction, transformation, and loading to improve pipeline efficiency. •Optimize data processing workflows for performance, reducing processing time and resource consumption. •Troubleshoot and resolve performance bottlenecks in data pipelines. 6. Collaboration with Data Teams: •Work closely with Data Scientists, Analysts, and business teams to understand data requirements and ensure the correct data is available and accessible. •Assist Data Scientists with preparing datasets for model training and deployment. •Provide technical expertise and support to ensure the integrity and consistency of data across all projects. 7. Data Quality Assurance: •Implement data validation checks to ensure data accuracy, completeness, and consistency throughout the pipeline. •Develop and enforce data quality standards to detect and resolve data issues before they affect analysis or reporting. •Monitor and improve data quality by identifying areas for improvement and implementing solutions. 8. Monitoring and Maintenance: •Set up monitoring and logging for data pipelines to detect and alert for issues such as failures, data mismatches, or delays. •Perform regular maintenance of data pipelines and storage systems to ensure optimal performance. •Update and improve data systems as required, keeping up with evolving technology and business needs. 9. Documentation and Reporting: •Document data pipeline designs, ETL processes, data schemas, and transformation logic for transparency and future reference. •Create reports on the performance and status of data pipelines, identifying areas of improvement or potential issues. •Provide guidance to other teams regarding the usage and structure of data systems. 10. Stay Updated with Technology Trends: •Continuously evaluate and adopt new tools, technologies, and best practices in data engineering and big data systems. •Participate in industry conferences, webinars, and training to stay current with emerging trends in data engineering and cloud computing. Qualifications: (Please list all required qualifications) Click here to enter text. (Rationalizes basic requirements for candidates to apply. Helps w/rationalization when Requirements: - 1. Educational Background: Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field 2. Technical Skills: •Proficiency in programming languages such as Python, Java, or Scala for data processing. •Strong knowledge of SQL and relational databases (e.g., MySQL, PostgreSQL, MS SQL Server). •Experience with NoSQL databases (e.g., MongoDB, Cassandra, HBase). •Familiarity with data warehousing solutions (e.g., Amazon Redshift, Google BigQuery, Snowflake). •Hands-on experience with ETL frameworks and tools (e.g., Apache NiFi, Talend, Informatica, Airflow). •Knowledge of big data technologies (e.g., Hadoop, Apache Spark, Kafka). •Experience with cloud platforms (AWS, Azure, Google Cloud) and related services for data storage and processing. •Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes) for building scalable data systems. •Knowledge of version control systems (e.g., Git) and collaboration tools (e.g., Jira, Confluence). •Understanding data modeling concepts (e.g., star schema, snowflake schema) and how they relate to data warehousing and analytics. •Knowledge of data lakes, data warehousing architecture, and how to design efficient and scalable storage solutions. 3.Soft Skills: •Strong problem-solving skills with an ability to troubleshoot complex data issues. •Excellent communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders. •Strong attention to detail and a commitment to maintaining data accuracy and integrity. •Ability to work effectively in a collaborative, team-based environment. 4.Experience: -3+ years of experience in data engineering, with hands-on experience in building and maintaining data pipelines and systems. - Proven track record of implementing data engineering solutions at scale, preferably in large or complex environments. - Experience working with data governance, compliance, and security protocols. 5.Preferred Qualifications**: -Experience with machine learning and preparing data for AI/ML model training. -Familiarity with stream processing frameworks (e.g., Apache Kafka, Apache Flink). -Certification in cloud platforms (e.g., AWS Certified Big Data - Specialty, Google Cloud Professional Data Engineer). -Experience with DevOps practices and CI/CD pipelines for data systems. -Experience with automation and orchestration tools (e.g., Apache Airflow, Luigi). -Familiarity with data visualization and reporting tools (e.g., Tableau, Power BI) to support analytics teams 6.Work Environment: •Collaborative and fast-paced work environment. •Opportunity to work with state-of-the-art technologies. •Supportive and dynamic team culture EOE: Our client is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind: We are committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at our client are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV Status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. We will not tolerate discrimination or harassment based on any of these characteristics.

$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!

Job Title - Data Engineer Location: Seattle, Santa Monica, New York, or San Francisco/Onsite/ Hybrid 4 days per week Type: Fulltime Type: Fulltime Key Points: Experience with Scala or Python? DataBricks/Hadoop Spark AIrflow SQL Experience with Snowflake and how have you used it in past projects Experience in data modelling Are they open for the HackerRank test Basic Qualifications: 5+ years of relevant data engineering experience. Strong understanding of data modeling principles including Dimensional modeling, data normalization principles. Good understanding of SQL Engines and able to conduct advanced performance tuning. Ability to think strategically, analyze and interpret market and consumer information. Strong communication skills - written and verbal presentations. Excellent conceptual and analytical reasoning competencies. Comfortable working in a fast-paced and highly collaborative environment. Familiarity with Agile Scrum principles and ceremonies Preferred Qualifications - 2+ years of work experience implementing and reporting on business key performance indicators in data warehousing environments, required. 2+ years of experience using analytic SQL, working with traditional relational databases and/or distributed systems (Snowflake or Redshift), required. 1+ years of experience programming languages (e.g. Python, Pyspark), preferred. 1+ years of experience with data orchestration/ETL tools (Airflow, Nifi), preferred. Experience with Snowflake, Databricks/EMR/Spark, and/or Airflow. Required Education - Degree in computer science, information systems Additional Information - Onsite/ Hybrid 4 days per week - in order of preference: Seattle, Santa Monica, New York or San Francisco. Intake Notes: Development experience with Airflow, Snowflake, and Databricks. At least five years of relevant recent experience with the mentioned tech stack. Proficiency in Python, as the interview process includes a Python coding test on HackerRank.

***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.

At GAF, we cover more than buildings. We cover each other. No matter what role, tenure, or track, under this roof you are empowered to be there for your teammates, your customers, and especially your community. Under this roof, we don't back down from hard work- we support one another in pursuit of something bigger. We define the future while leading the present. And under this roof, we own our opportunities. Becoming the market leader only happens when everyone feels they have the opportunity, and the support, to thrive. We are GAF. And under this roof, we protect what matters most. **Job Summary** As part of a team, develop advanced analytical models to solve business problems leveraging the latest technologies in statistical and Artificial Intelligence (AI) models to achieve organizational goals, increase data-driven insights, functional excellence, and digital expertise. **Essential Duties** + 60% Data Modeling + Transform business problems into data science cases to assess the scope of model's value, speed, and cost in order to articulate model selection criteria. + Build Data Science models using cloud-computing platforms such as AWS, Azure, and Google. + Build Data Science models using any relevant Data Science capability. + Be prepared to automate analytical workflows. + Manage and shape modeling design, development, and delivery process. + 20% Data Collection + Collect, profile, collate, and map appropriate data for usage in new or existing solutions as well as for ongoing data analysis activities. + Develop, maintain, and review data processes and architecture for both on-premise and cloud-based data systems. + Develop and perform standard queries to ensure data quality, identify data inconsistencies, missing data and resolve as needed. + Perform data extraction, storage, manipulation, processing, and analysis. + Conduct programmatic web scraping to acquire external publicly available information. + 20% Model Deployment and Evaluation + Assemble relevant User Interfaces (UIs) or Dashboards. + Assemble, deliver, and effectively communicate actionable insights for decision-makers. **Under This Roof We Require** + Bachelor's Degree Data Science Academy in a related technical Data Science discipline. + 5 or more years of relevant experience **Under This Roof We Also Value** + Master's degree Data Science Academy in a related technical Data Science discipline. **General Knowledge, Skills and Abilities** + Teamwork: Collaborates with other members of formal and informal groups in the pursuit of a common mission, vision, values and mutual goals. + Change Advocate: Identifies and acts upon opportunities for continuous improvement. + Communicates for Results: Expresses technical and business concepts, ideas, feelings, opinions, and conclusions orally and in writing. + Conceptual Thinking: Applies appropriate concepts and theories in the development of principles, practices, techniques, tools and solutions. + Information Seeking: Gathers and analyzes information or data on current and future trends of best practice. + Innovation: Employs sound judgment in determining how innovations will be deployed to produce return on investment. + Problem Solving: Anticipates, identifies and defines problems; seeks root causes. + (Advanced) Data intuition. + (Intermediate) General experience across relevant business operations to enhance understanding would be desirable. + (Entry) Exposure to roofing or manufacturing industry would be helpful **Technical Knowledge, Skills and Abilities** + (Advanced) Python, R, or other relevant Data Science capabilities + (Intermediate) SQL, NoSQL, & Hadoop + (Entry) Any Data or visualization tool or software + (Entry) Web Scraping: Scrapy, bsa, selenium, spiders, and API calls. Consideration will be given based on geography, candidate experience, and qualifications. Annual Salary Range: 135,000-172,500 **How We Protect What Matters Most:** 1. We offer a wide range of health insurance options that include medical, dental, and vision for you and your family. 2. Our Family-Building benefits support the many different journeys to fertility and parenthood. 3. Our robust 401K plan includes an employer match contribution with your pre-tax and/or Roth contributions. 4. Other exciting programs and perks are available to help employees achieve work-life balance, including (but not limited to) a wellness program, free financial coaching, a referral program, and product rebates when purchased for an employee's primary residence. 5. Professional growth and development are very important to us! We offer internal training programs and courses, as well as a generous tuition reimbursement program. 6. We put diversity and inclusion into action with our Employee Resource Groups, which unite employees based on common perspectives, identities, demographic factors, or out of a desire to be an ally. GAF complies with federal, state, and local disability laws and makes reasonable accommodations for applicants and employees with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact HR Services at 833-HR-XPERT. We believe our employees are our greatest resource. We offer competitive salary, benefits, 401k, and vacation packages for all full time permanent positions. We are proud to be an equal opportunity workplace and GAF, Standard Logistics, SGI, and Siplast are proud to be affirmative action employers. 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. If you have a disability or special need that requires accommodation, please let us know. If applying for positions in the U.S., must be eligible to work in the U.S. without need for employer sponsored visa (work permit). Privacy Policy (******************************************************************** **CA Privacy** Applicant Notice (****************************************************************************** With 130+ years in the industry, GAF is the leading roofing manufacturer in North America. As a member of the Standard Industries family of companies, we are also part of the largest roofing and waterproofing business in the world. Our communities help give our work meaning and the products we manufacture help protect what matters most. The shingles help to shelter the families living in the homes in our towns. The TPO helps protect what is under that hospital's roof. In addition to quality products, we make sure they are installed by quality craftsmen and women. The full GAF portfolio of solutions is supported by an extensive national network of factory-certified contractors. GAF continues to be the leader in quality and offers comprehensive warranty protection on its products and systems. Our success is driven by a commitment to empowering our people to deliver advanced quality and purposeful innovation and the desire to protect what matters most.

Overview Responsibilities The Provider Data Analyst is responsible for the maintenance of the DHMSO Provider Data Network within EZCAP. The maintenance includes creating new provider records updating existing provider records and working with the Contracting and Credentialing teams as needed when questions arise. The Provider Data Analyst partners with Configuration Claims and Enrollment to ensure end to end accuracy to pay claims accurately and timely. Qualifications Minimum Qualifications: Minimum of 3 years experience managing provider data and working in EZCAP. Proven ability to work with other business functions. Working knowledge of DHPR and CMS rules for Claim. Submission, Claim Payment, Eligibility, Appeals for Commercial, MediCare and MediCal lines of business. Bachelor's Degree - Bachelor's Degree or equivalent experience.

Would you like to join an international team working to improve the future of healthcare? Do you want to enhance the lives of millions of people? Grifols is a global healthcare company that since 1909 has been working to improve the health and well-being of people around the world. We are leaders in plasma-derived medicines and transfusion medicine and develop, produce and market innovative medicines, solutions and services in more than 110 countries and regions. **Summary:** The Senior Data Engineer will oversee the business unit's data integration work, including developing a data model, maintaining a data warehouse and analytics environment, and writing scripts for data integration and analysis. Responsible for designing, developing, and maintaining data pipelines, ensuring data quality, and enabling data-driven decision-making processes. **Primary responsibilities for role:** + Independently lead analytical development to extract hidden insights from Real World Medical Data + Independently identify insights from data and metadata sources, interpreting and communicating findings to management + Ensure completeness, critical evaluation, correctness and integrity of analyses and datasets + Lead and advise integration of internal and external needs and capabilities of internal RWD team and external vendors; manage vendor process changes that require team to continuously reformat or set up new environments (ie. Snowflake) + Established, maintains and enforces our data pipeline standards and conventions + Establishes and maintains our data engineering documentation + Manages our data pipeline codebase using external source control repositories as well as within-product tools (e.g., Databricks notebooks) + Works on significant and unique issues where analysis of situations or data requires an evaluation of intangibles + Determines methods and procedures on new assignments + Networks with key contacts outside own area of expertise + Exercises judgment in selecting methods, evaluating, adapting of complex techniques and evaluation criteria for obtaining results + Accountable for results, which may impact the entire function + Supervises and manages vendors and external consultant(s) + Serve internally as a subject matter expert; advises others on complex matters **Additional Responsibilities:** + Work closely with teams across biostatistics, data science, data engineering and cloud operations to design and implement data initiatives based on understanding of their use cases + Data Governance: Establishes, modifies, and documents data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data + Provide guidance and hands-on support with real world data management and analysis (real world data can include EHRs, claims, wearables, questionnaires, imaging data, etc.) + Engage external resources to apply cutting edge methodologies and ensure recognition in the scientific community including publications + Stay abreast of emerging trends and advancements in data engineering, and software development to continually enhance our research and development operations **Knowledge, Skills, and Abilities:** + Must be a delivery-focused engineer who is passionate about leveraging technology for meaningful and impactful applications + Ability to rapidly develop and iterate on proofs-of-concept to test new ideas and hypotheses to efficiently validate and evolve software solutions in alignment with strategic Company objectives + Proficient with data science tools such as R, R data pipelining tools (e.g., Posit connect) and Python libraries (PyTorch, Scikit-Learn, SciPy) + Must have excellent written and oral communication skills to convey advanced information and persuade several diverse stakeholders/audiences + Deep understanding of complex data, data curation and data quality, such as traceability, security, performance latency and correctness across supply and demand processes. + Background in SQL and cloud infrastructure such as S3, ECS, EMR, Lambda, Glue as well as expertise with some core data technologies such as of Trino, Presto, Parquet, Hudi, Iceberg + Exceptional collaboration and communication skills to effectively engage and work with stakeholders from diverse disciplines and varying levels of technical expertise. Ideally, adept at translating complex technical concepts into clear, actionable insights for all audiences. + Experience in data engineering using R and Python (or other software toolkits), with a demonstrated ability to thrive in ambiguous and rapidly changing environments + Proficient with data science tools such as R, R data pipelining tools (e.g., Posit connect) and Python libraries (PyTorch, Scikit-Learn, SciPy) **Education:** Bachelor's or Master's degree in Computer Science, Engineering, or a related field **Experience:** 8+ years of relevant experience with a Bachelor's degree **Equivalency:** 6 years and a Master's degree; or 3 years with a PhD; or 12 years of related experience **Pay Scale:** The estimated pay scale for the Sr. Data Engineer role based in the United States (non-California), is $114,000.00-$148.000.00 per year. Additionally, the position is eligible to participate in the company bonus pool. We offer a wide variety of benefits including, but not limited to: Medical, Dental, Vision, PTO, 9 paid Holidays per year, up to 5% 401(K) match and tuition reimbursement. Final compensation packages will ultimately depend on education, experience, skillset, knowledge, where the role is performed, internal equity and market data. We are committed to offering our employees opportunities for professional growth and career progression. Grifols is a global healthcare organization with employees in 30 countries focused on patient health and providing impactful results. Since our humble beginnings in 1909, Grifols has been a family company that prides itself on its family-like culture. Our company has more than tripled over the last 10 years, and you can grow with us! **For California:** The estimated pay scale for the Sr. Data Engineer role based in San Francisco, San Carlos or Emeryville, California, is $140,000.00- $185,000.00 per year. The estimated pay scale for the Sr. Data Engineer role based in all other cities in California is $130,000.00 - $170,200.00 per year. **For Washington State:** Currently, the first year PTO accrual for this role is 120 hours per year. Then, after completion of 365 days of employment the PTO accrual for this role will increase to 160 hours per year. Third Party Agency and Recruiter Notice: Agencies that present a candidate to Grifols must have an active, nonexpired, Grifols Agency Master Services Agreement with the Grifols Talent Acquisition Department. Additionally, agencies may only submit candidates to positions that they have been engaged to work on by a Grifols Recruiter. All resumes must be sent to a Grifols Recruiter under these terms or they will be considered a Grifols candidate. **Grifols provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other characteristic or status protected by law. We will consider for employment all qualified Applicants, including those with arrests or conviction records, in a manner consistent with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and City of Los Angeles' Fair Chance Initiative for Hiring Ordinance.** Learn more about Grifols (************************************** **Req ID:** 521347 **Type:** Regular Full-Time **Job Category:** Research & Development

The purpose of Dignity Health Management Services Organization (Dignity Health MSO) is to build a system-wide integrated physician-centric full-service management service organization structure. We offer a menu of management and business services that will leverage economies of scale across provider types and geographies and will lead the effort in developing Dignity Health's Medicaid population health care management pathways. Dignity Health MSO is dedicated to providing quality managed care administrative and clinical services to medical groups hospitals health plans and employers with a business objective to excel in coordinating patient care in a manner that supports containing costs while continually improving quality of care and levels of service. Dignity Health MSO accomplishes this by capitalizing on industry-leading technology and integrated administrative systems powered by local human resources that put patient care first.Dignity Health MSO offers an outstanding Total Rewards package that integrates competitive pay with a state-of-the-art flexible Health & Welfare benefits package. Our cafeteria-style benefit program gives employees the ability to choose the benefits they want from a variety of options including medical dental and vision plans for the employee and their dependents Health Spending Account (HSA) Life Insurance and Long Term Disability. We also offer a 401k retirement plan with a generous employer-match. Other benefits include Paid Time Off and Sick Leave. **Responsibilities** The Provider Data Analyst is responsible for the maintenance of the DHMSO Provider Data Network within EZCAP. The maintenance includes creating new provider records updating existing provider records and working with the Contracting and Credentialing teams as needed when questions arise. The Provider Data Analyst partners with Configuration Claims and Enrollment to ensure end to end accuracy to pay claims accurately and timely. **Qualifications** **Minimum Qualifications:** + Minimum of 3 years experience managing provider data and working in EZCAP. Proven ability to work with other business functions. Working knowledge of DHPR and CMS rules for Claim. Submission, Claim Payment, Eligibility, Appeals for Commercial, MediCare and MediCal lines of business. + Bachelor's Degree - Bachelor's Degree or equivalent experience. **Pay Range** $25.25 - $36.61 /hour We are an equal opportunity/affirmative action employer.

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.