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Salary: USD 163,944 - 215,176.5 / annual
Oscar Health is seeking a Senior Data Scientist, Pharmacy to join its Data team. Oscar is a technology-first health insurance company founded in 2012, built around a full-stack platform with a focus on member experience and affordability.
In this role, you will support Oscar's pharmacy benefit by developing data pipelines, models, and analytics that improve medication access, member experience, and plan affordability. You will work cross-functionally with clinical, business, product, and engineering partners to lead projects in formulary optimization, utilization and population need trend analytics, and prior authorization automation.
Key responsibilities include:
- 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.
- Collaborate closely with data leaders and business teams to enhance overall data processes and lead execution. 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.
Work location: Hybrid in New York City office, requiring 3 days per week in-office. Thursdays are mandatory for team meetings and events; the other two office days are flexible.
Requirements:
- Bachelor's degree or 6+ years of industry or educational experience in a technical field
- 4+ years of work experience with SQL, R, and/or Python to query, manipulate, and analyze data
- 4+ years of experience building data models and using advanced analytics methods, including in-depth analysis beyond simple descriptive 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 qualifications:
- 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
- Master's degree in a quantitative field plus 3 years of relevant experience, or PhD in a quantitative field
