Senior Data Scientist, Pharmacy

About the Role

The Senior Data Scientist, Pharmacy position supports our pharmacy benefit, developing data pipelines, models, and analytics that improve medication access, member experience, and plan affordability. Working with clinical, business, product, and engineering partners, you will lead projects in formulary optimization, utilization and population need trend analytics, and prior authorization automation.

Work Location: Based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible.

Responsibilities

• Design and develop clinical AI and ML applications, leading the experimental lifecycle, target development, and operationalization strategy. Apply rigorous data science practices to ensure performance is robustly measured, safety and observability are prioritized, and deployment decisions are grounded in clear clinical and operational success criteria.
• Apply advanced analytics to evaluate complex financial and health outcome questions, helping partners understand the potential effects of changes to clinical policies, benefit design, and member programs. Develop models and scenario analyses to quantify tradeoffs, test assumptions, and characterize uncertainty, translating findings into actionable recommendations. Validate analytical methods and results to ensure conclusions are robust and appropriate for the decisions they inform.
• Collaborate closely with data leaders and business teams to enhance overall data processes, and lead execution with your team. Understand their needs and requirements, provide data support, and work together to develop solutions that improve processes and outcomes. Partner with business and technical stakeholders to prioritize opportunities, define success metrics, and guide experiments through evaluation and implementation.
• Ensure compliance with all applicable laws and regulations.
• Other duties as assigned.

Requirements

• A bachelor's degree or 6+ years of industry or educational experience in a technical field.
• 4+ years of work experience working with SQL, R, and/or Python to query, manipulate and analyze data.
• 4+ years of experience building data models and using more advanced analytics methods, including conducting in-depth analysis.
• 4+ years of experience with statistical modeling and data processing/ETL pipeline building.
• 2+ years of experience working with and presenting to non-technical stakeholders.

Bonus Points

• Experience in healthcare, finance, or insurance industries, particularly pharmacy benefits or clinical operations.
• Experience developing and deploying AI/ML applications involving unstructured documents, with rigorous evaluation and production monitoring.
• Experience using statistical modeling to evaluate utilization trends, program effectiveness, or financial and health outcome tradeoffs, quantifying uncertainty.
• A master’s degree in a quantitative field plus 3 years of relevant experience, or a PhD in a quantitative field.