Senior Data Scientist

About the role

The Senior Data Scientist, Risk Adjustment at Oscar Health owns the conversion of complex healthcare and insurance information into actionable intelligence that directly informs financial strategy and operational decisions. In this capacity, you will lead projects from initial scoping through final deployment, replacing manual workflows with robust, accurate, and feature-rich production systems. You will design technical solutions in collaboration with Actuarial and Risk Adjustment partners, translating ambiguous ideas into validated, maintainable systems using a builder's mindset. A core part of the role involves constructing models, pipelines, and systems that measure clinical risk and support risk adjustment submissions on a fully engineered scale. You will guide the technical strategy of the data science team while mentoring junior data scientists and shaping model infrastructure. The position requires deep collaboration across functions to refine data products and influence roadmap decisions based on analytical insights. You will ensure all efforts comply with regulations governing healthcare data and contribute to Oscar's member-first service philosophy. This role is critical in transforming detailed product interactions, financial claims, and clinical records into reliable intelligence.

Key facts

What you'll do

• Scope complex challenges in partnership with Actuarial and Risk Adjustment stakeholders to define precise technical approaches for risk adjustment initiatives.
• Construct scalable and reliable data pipelines using SQL and Python to process financial claims, clinical records, and detailed product interactions for analytical modeling.
• Design and implement advanced statistical and machine learning models that measure clinical risk and strengthen Oscar's risk adjustment submissions.
• Validate model outputs against existing methods and iterate on deployed systems to ensure continuous improvement and accuracy in production environments.
• Replace legacy manual workflows with automated, feature-rich systems that are efficient, robust, and aligned with Oscar's operational needs.
• Re-engineer processes to enhance reliability and efficiency while adhering to standards for healthcare data compliance and regulatory requirements.
• Mentor junior data scientists and contribute to the team's technical strategy by shaping model infrastructure and guiding data product development.
• Collaborate cross-functionally with partners to refine data products and impact strategic roadmap decisions based on analytical findings and business priorities.
• Build and maintain production-grade data systems that integrate version control, testing, and code review to ensure quality and maintainability.
• Translate intricate healthcare and insurance information into actionable intelligence that supports Oscar's member-first service philosophy and financial objectives.
• Own the end-to-end lifecycle of risk adjustment data projects from initial planning through deployment and post-launch monitoring.
• Work directly with Actuarial teams to understand manual processes and translate them into automated, scalable data solutions.
• Utilize SQL and Python to build data models that capture clinical risk and support decision-making across the organization.
• Ensure all data products and models align with regulations governing healthcare data and insurance operations.

Requirements

• Bring three or more years of experience using SQL and Python for data manipulation, analysis, and modeling in a production environment.
• Demonstrate the ability to build data models using advanced statistical methods and processing workflows that scale.
• Show proven experience designing production-grade pipelines that incorporate version control, testing, and code review practices.
• Hold a strong quantitative background, often evidenced by an advanced degree in a related field such as statistics, data science, or analytics.
• Exhibit prior experience in healthcare, finance, or insurance environments to understand industry-specific challenges and constraints.
• Display familiarity with risk adjustment methodologies and actuarial processes to effectively contribute to risk adjustment submissions.
• Possess knowledge of insurance products and regulatory environments to ensure compliance and accuracy in data solutions.
• Apply core tools including Python, SQL, and statistical modeling frameworks to solve complex problems and build reliable systems.
• Work with data models, risk adjustment methodologies, and pipeline architecture to create maintainable and efficient solutions.
• Commit to compliance with regulations governing healthcare data as a standard duty in daily work activities.

Nice to have

• Preferred experience working within health coverage environments that rely on technology-driven platforms similar to Oscar's member-first approach.
• Exposure to transforming detailed product interactions and claims data into strategic intelligence for financial and operational decision-making.

Practical notes

This role is based in our New York City office. The schedule is hybrid, requiring three days onsite. Thursdays are mandatory for team collaboration, while the remaining days offer flexibility.