Chief Data Scientist - UnitedHealthcare

At UnitedHealthcare, we're simplifying the health care experience, creating healthier communities and removing barriers to quality care. The work you do here impacts the lives of millions of people for the better. Come build the health care system of tomorrow, making it more responsive, affordable and optimized. Ready to make a difference? Join us to start Caring. Connecting. Growing together.

The UnitedHealthcare Chief Data Scientist is a strategic leader responsible for establishing a new data science capability with the remit to transform data, advance analytics and AI into measurable enterprise value across the healthcare insurance ecosystem. This role ensures that advanced predictive analytics directly supports core business objectives, including affordability, quality of care, member experience, financial and actuarial planning and operational efficiencies. The Chief Data Scientist operates at a senior level and partners with senior UnitedHealthcare business leaders to identify high-impact transformative opportunities and deliver solutions that drive impact. The senior leader will work cross functionally with the UnitedHealth Group and Optum teams to secure efficient, scalable and sustained solution design and deployment.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

Hybrid in MN/DC: This position follows a hybrid schedule with four in-office days per week.

Primary Responsibilities:

UnitedHealthcare Strategy & Business Alignment

• Collaborate with executive leaders across Financial, Actuarial, Healthcare Economics, Operations, Provider and Member Experience organizations to translate strategy into a prioritized data science roadmap with enhanced predictive capabilities
• Identify and champion opportunities where AI and predictive analytics can improve care affordability, enhance population health management, optimize medical costs insights and signaling and streamline data and insights pipeline operations
• Communicate analytical and predictive insights in clear, actionable terms to support strategic decisions and planning - not in technical terms

Value Creation in Focus

• Lead development of value frameworks that quantify outcomes such as medical cost savings, improved quality scores, risk accuracy, utilization management efficiencies, financial forecasting, reserving and provider network performance

• Ensure all predictive models and analytics directly improve key metrics and regulatory, legal and compliance performance

Applied AI Transformation Across the Insurance Lifecycle

• Drive end-to-end AI/ML development across connected data domains of claims, member, provider and networks

• Enhanced Forecasting Capabilities: Predictive models for early detection, medical cost trends, member behavior insights and member population stratification

• Support Utilization Management & Care Management: Influence models to automate prior authorization, detect avoidable utilization and target members for care coordination

• Provider Network Optimization: Predictive insights to manage provider performance, leakage, cost variation and contracting opportunities

• Member Engagement & Experience: Personalization models that improve retention, adherence and satisfaction

• Payment Integrity & FWA: Advanced anomaly detection and claims pattern analytics and predictions

• Deliver high-quality and contemporary data science models that are explainable, compliant and integrated into real-world workflows

Operationalization & Cross-Functional Collaboration

• Partner with Technology, Clinical Operations, Claims, Actuarial and Product teams to deploy and scale AI solutions across the enterprise
• Embed data science resources within key business areas to maximize adoption and impact
• Ensure seamless integration of models into products, workflows and decision-support systems

Leadership & Talent Development

• Build and lead a high-performing, multidisciplinary team of data scientists, data engineering experts, machine learning engineers and AI product partners
• Foster a culture of innovation, collaboration and influence grounded in healthcare ethics and member-first principles
• Strengthen data literacy across UHC, empowering leaders to make informed decisions

Success Measures

• Recognized improvement in medical cost trend forecasting and improved affordability
• Increased automation and efficiency across data and insights operations
• Scaled adoption of AI-enabled insights across business units
• Strong governance, compliance readiness and responsible AI maturity
• High engagement, retention and growth within the data science team

Technical Expertise

Machine Learning & Advanced Analytics

• Predictive modeling (classification, regression, survival analysis)
• Ensemble methods, gradient boosting, random forests and XGBoost/LightGBM
• Deep learning (NLP, sequence models, representation learning)
• Probabilistic modeling and Bayesian methods
• Time-series forecasting (claims trend, utilization, membership, RAF forecasting)
• Causal inference and uplift modeling for interventions and care programs

Productization of Data Science & AI

• Building analytic products (risk engines, utilization predictors, network tools)
• Designing feedback loops for continuous improvement
• A/B testing and impact measurement in operational workflows
• Integrating AI into digital member, provider experiences and internal workflows

Insurance Data Expertise

• Claims data (medical, pharmacy, behavioral, dental)
• EHR/clinical data, lab results, clinical notes
• Risk adjustment models
• Quality measurement frameworks
• Social determinants of health data integration
• Provider data: NPI, cost/quality variation, contracting data

Natural Language Processing (NLP)

• Clinical document processing (progress notes, medical records, appeals)
• Claims and prior authorization text extraction/automation
• Named entity recognition for diagnoses, procedures, risk factors
• Large language models (LLMs) for summarization, routing, code capture, member communication

AI/ML Engineering & Deployment

• Model operationalization and MLOps
• Feature stores, model registries, and artifact tracking
• Model monitoring (drift, bias, performance, retraining)
• Building scalable AI services/APIs for production
• Real-time inference and decision-support integration
• Cloud ML platforms knowledge

Data Engineering

• Data warehousing and lakehouse platforms (Databricks, Snowflake knowledge)
• Data pipelines for high-volume claims and clinical data
• Data modeling for healthcare operations (member, provider, claims)

Preferred Programming & Tools knowledge

• Python (pandas, scikit-learn, PyTorch, TensorFlow)
• SAS (STAT, ETS and OR)
• R (useful for actuarial, risk, quality analytics)
• Spark/PySpark
• Visualization and BI platforms (Power BI)

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

• 15+ years of proven executive leadership experience in advanced analytics, insurance operations, actuarial science or/and applied AI
• Deep understanding of the insurance ecosystem, including medical cost drivers, regulatory frameworks, claims workflows and quality performance metrics
• Proven track record of delivering data science and AI solutions that drive measurable financial and clinical impact
• Solid expertise in predictive modeling, machine learning, data and analytical solution design
• Expect level experience linking a business problem to applied data science techniques leading the hands-on technical talent in model development
• Solid communication and partnership skills, with ability to align complex analytics to business and financial outcomes
• Ability to demonstrate value-based leadership aligned to UnitedHealth Group culture and hire, grown and retain data science talent for future success
  
  

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $225,000 to $375,000 annually based on full-time employment. We comply with all minimum wage laws as applicable.

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

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.