Role Description As a Senior Data Scientist of Medicaid Quality Analytics (UHC Government Programs), you will maintain and continue to reimagine the foundational metrics and analytics surrounding quality at UHG, making them more actionable, transparent, accurate, and flexible. The role will integrate new relationships around the company, new data sources, and new methods/technology along the way. We are seeking an experienced Senior Data Scientist to support our value-based care program in Medicaid lines of business. You will serve as the primary analytical partner to our strategy and partner team, translating complex program requirements into rigorous data models, actionable insights, and implementable solutions. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities: - Develop analytical frameworks to support program design decisions and implementation - Perform data analytics to identify insights that can be incorporated into strategic recommendations for improving member care and to drive quality measure performance improvements - Apply causal inference methodologies to evaluate program impact and generate insights to inform future program design iterations - Collaborate with analytics, reporting, network management, and business stakeholders to deliver scalable, high-impact solutions - Clearly communicate findings and recommendations to a range of stakeholders - Proactively communicate risks, trade-offs, and limitations of analytical approaches Qualifications - 3+ years of professional experience developing analytical solutions using techniques such as machine learning, simulations, hypothesis testing, experimental design etc. - 3+ years of professional experience with SQL, Python, PySpark and large-scale cloud-based data platforms (e.g., Snowflake, Databricks) - Advanced level of problem-solving skills and the ability to collaborate effectively across cross-functional teams Requirements - Bachelor’s Degree (or higher) in a quantitative field such as Statistics, Health Economics, Mathematics, Computer Science, or related disciplines - Strong understanding of Medicaid/DSNP products or the healthcare industry - Strong relationship building skills with internal stakeholders and operational teams to drive alignment and outcomes - Strong communication skills, with the ability to present program objectives, processes, and performance to diverse audiences Benefits - Comprehensive benefits package - Incentive and recognition programs - Equity stock purchase - 401k contribution (all benefits are subject to eligibility requirements) Company Description At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location, and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups, and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment.

Role Description The Lead Data Scientist will be integral as we continue to bring innovative new products to market in response to client needs and opportunities. The Lead Data Scientist will build upon their data science, machine learning, and/or GenAI and Natural Language Processing (NLP) expertise to develop intimate knowledge of our current product capabilities and provide advanced analytical expertise to enhance these products through new solutions. Projects will include construction, validation, documentation and delivery of sophisticated GenAI and machine learning solutions for a variety of healthcare-related problems. The key area of responsibility in the role of Lead Data Scientist is to work in conjunction with our business development and product teams to develop and implement commercially viable model-based solutions to the healthcare, insurance, life sciences and adjacent markets. - Research, develop, deploy, and maintain traditional AI/ML models following industry best practices. - Work extensively with available GenAI models; construct exciting solutions to internal and external use cases across markets and enhance our internal capabilities through centralized internal tooling and thought leadership. - Coordinate with Product, Business Development, ML Engineering, and IT to bring new and exciting data science products to market, as well as support existing industry leading products. - Help drive best practices and continuous improvement on the data science team; influencing model design and experimentation strategy through planning, audit, peer review, and other coaching. Qualifications - 10+ years of professional experience using AI/ML to create high return on investment commercial data science solutions. - Expertise with Electronic Health Records or unstructured data analysis. - Expert data scientist with demonstrable capability building traditional AI/ML models. - Supervised Learning: Linear/logistic regression, decision trees, random forests, gradient boosting (XGBoost, LightGBM, CatBoost), and ensemble methods. - Unsupervised Learning: K-means clustering, hierarchical clustering, PCA, and anomaly detection algorithms. - Model Validation: Cross-validation strategies, hyperparameter optimization (Grid Search, Random Search, Bayesian optimization), and A/B testing frameworks. - Deep Learning Architectures: Neural networks, transformers, and transfer learning methodologies. - NLP Algorithms: Text preprocessing, TF-IDF, word embeddings (Word2Vec, GloVe), topic modeling (LDA), sentiment analysis, and named entity recognition. - Expert understanding of NLP and generative AI; able to effectively use, fine-tune, and evaluate commercially available models as well as deploy and integrate local LLMs into the data science process. - Hands-on experience building GenAI applications (e.g., RAG systems, LLM evaluation frameworks, or GenAI-powered internal tools). - Expert level Python programmer, with some experience in R and/or SQL. - Expert user of Databricks or similar cloud-based model development ecosystem including mlflow, experimentation organization, data catalogs, and compute cluster configuration. - Sufficient understanding of software engineering best practices such as Git for version control, unit testing, local development, and environment management. - Knowledge of ML Engineering and ML Ops related concepts and tools including CICD pipelines, GitHub Actions, Docker, AWS Lambda, and Linux. - Degree in a relevant field (computer science, data science, statistics, mathematics, applied math, actuarial science, economics, etc.). Requirements - Excellent communication skills, in person and through phone/email. - Proven ability to understand client analytical needs, translate them into an action plan, then execute and deliver. - Customer-centric approach to finding solutions. - Focused on results and able to explain findings in a way that answers business problems. - Constructive, “can do” approach to overcoming obstacles. - Can quickly learn new techniques and technologies. - Proactive in identifying process improvements. - Strong work ethic, willing to pitch in wherever needed. - Thrive in a small team, without micromanagement. - Ability to manage projects and timelines, including directing the work of others. Wish List - PhD in relevant field or Actuarial designation (FCAS/FSA). - Experience in one of the following industries: healthcare, insurance (L&H or P&C), finance, life sciences, or similar fields. - Experience at an InsurTech or FinTech. - Past experience working in a HIPAA / PHI / PCI compliant environment. Location The expected application deadline for this job is December 31, 2026. This position is open to remote work. Applicants must be willing to travel to the Milliman office in Brookfield, WI as needed and travel nationwide for meetings, conferences, and team events. Compensation The overall salary range for this role is $117,500 - $249,780. - For candidates residing in Alaska, California, Connecticut, Illinois, Maryland, Massachusetts, New Jersey, New York City, Pennsylvania, Virginia, Washington, or the District of Columbia: - $135,125 - $222,985 if overall experience is less than 15 years; - $151,340 - $249,780 for experience greater than 15 years. - All other states: - $117,500 - $193,900 if overall experience is less than 15 years; - $131,600 - $217,200 for experience greater than 15 years. Benefits - Medical, Dental and Vision – Coverage for employees, dependents, and domestic partners. - Employee Assistance Program (EAP) – Confidential support for personal and work-related challenges. - 401(k) Plan – Includes a company matching program and profit-sharing contributions. - Discretionary Bonus Program – Recognizing employee contributions. - Flexible Spending Accounts (FSA) – Pre-tax savings for dependent care, transportation, and eligible medical expenses. - Paid Time Off (PTO) – Begins accruing on the first day of work. Full-time employees accrue 15 days per year, and employees working less than full-time accrue PTO on a prorated basis. - Holidays – A minimum of 10 paid holidays per year. - Family Building Benefits – Includes adoption and fertility assistance. - Paid Parental Leave – Up to 11 weeks of paid leave for employees who meet eligibility criteria. - Life Insurance & AD&D – 100% of premiums covered by Milliman. - Short-Term and Long-Term Disability – Fully paid by Milliman. Equal Opportunity All qualified applicants will receive consideration for employment, without regard to race, color, religion, sex, sexual orientation, national origin, disability, or status as a protected veteran.

• Own the quality strategy, operating model, and execution plan for AI Data Services. • Build and standardize QA frameworks, audit models, scorecards, sampling approaches, and acceptance criteria. • Define critical, major, and minor error classifications across different data workflows. • Lead quality governance for strategic customer programs, including reporting, calibration, escalations, and remediation. • Partner with Operations, Program Management, Supply Chain, Solutions, and Sales to ensure quality requirements are clearly understood and operationally feasible. • Develop root cause analysis, corrective action, and continuous improvement processes. • Build quality dashboards, customer-facing reporting, and internal quality performance views. • Support the creation of SOPs, reviewer guidelines, calibration materials, and QA documentation. • Help improve delivery consistency, reduce rework, and strengthen customer confidence. • Mentor and guide QA managers, auditors, reviewers, and quality specialists as the team scales.

Role Description At Coursera, our Data Science team is helping to build the future of education through data-driven decision-making and data-powered products. We drive product and business strategy through measurement, experimentation, and causal inference to help Coursera deliver effective content discovery and personalized learning at scale. We believe the next generation of teaching and learning should be personalized, accessible, and efficient. With our scale, data, technology, and talent, Coursera and its Data Science team are positioned to make that vision a reality. We’re looking for a knowledgeable Data Scientist - Business Analytics to support decision-making for our business and consumer leadership teams. This role will be leveraging the rich data captured by over 200M+ learners and thousands of instructors engaging on the platform to identify business trends, define and track KPIs, and deliver data-driven insights that help shape consumer strategy. This role will partner closely with business leaders across the organization to align on strategic priorities and measure business performance. Our ideal candidate possesses strong analytical and reporting skills, familiarity with trend analysis and KPI frameworks, strong business acumen, and the ability to translate analysis into actionable recommendations that inform consumer and business strategy. - Develop a deep understanding of Coursera’s business, market, and learners to identify trends and translate them into actionable insights and recommendations. - Analyze business performance, define and track KPIs, and conduct deep dives into consumer behavior and business trends. - Partner with business leaders to shape consumer strategy and inform strategic prioritization. - Support analytics teams to build dashboards and reporting systems for tracking key business and consumer metrics. - Present findings and recommendations to business leaders and cross-functional partners clearly and concisely. Qualifications - Background in economics, statistics, data science, computer science, or a related technical field. - 3+ years of experience as a data scientist, data analyst, or business intelligence analyst. - Strong SQL skills and proficiency with at least one scripting language (e.g. Python, R). - Proficiency in BI tools (e.g. Sigma, Databricks, Looker, Tableau). - Excellent communication skills, with the ability to translate complex data findings into actionable insights. - Strong attention to detail and the ability to manage multiple projects simultaneously. Requirements - 5+ years of experience using data to advise business, marketing, or consumer strategy teams. - Advanced proficiency with SQL and Python to produce clear and actionable insights. - Experience leveraging AI tools to accelerate data analysis, generate insights, or enhance analytical workflows. - Familiarity with online education platforms, specifically with platforms like Coursera and Udemy. Compensation Our job titles may span more than one career level. The starting base pay for this role is between $113,600 CAD and $142,000 CAD. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs, and location. The base pay range is subject to change and may be modified in the future. This role is also eligible for bonus, equity, and benefits.