Hi, we're Oscar. We're hiring a VP of Analytics and Insights to join our Data Science team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

The VP of Analytics and Insights will be a pivotal leader, tasked with building and scaling the Analytics and Insights function to drive data-informed decision-making across the entire organization. This role requires championing both business strategy and the underlying data infrastructure, including the semantic and business data layers. A key responsibility is ensuring that insights are both actionable and underpinned by a robust engineering foundation. This leader will build and manage integrated teams of analysts, analytics engineers, and insights professionals (covering user, market, and other research competencies).

You will report into the SVP, Data.

Work Location: This position is based in our New York 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 to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $264,132 - $346,673 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants and annual performance bonuses.

Responsibilities:

• Function Buildout & Leadership: Lead the creation of a centralized, company-wide Analytics function, defining its vision, strategy, and roadmap to support all business units (e.g., Clinical, Product, Operations, Marketing, Strategy).
• End-to-End Ownership: Own the full lifecycle of data use cases, from identifying high-impact business questions to delivering compelling insights, while also managing the development and scalability of the analytics platform (including a platform engineering component).
• Insights and Research: Oversee the integrated Insights function, which includes dedicated teams for User Research and Market Research, to provide a holistic view of customer behavior, needs, and market trends.
• Innovation via AI: Drive the application of AI and machine learning techniques within the analytics ecosystem to uncover patterns, predict future outcomes, and inform strategic decisions that advance the future of health care.
• Team Development: Recruit, mentor, and lead a diverse, high-performing team of analysts, analytics engineers, user researchers, and market researchers.
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• Minimum: Bachelor’s degree in a quantitative or technical field (e.g., Data Science, Statistics, Computer Science, Economics, Mathematics, or Engineering).
• Leadership Breadth: 10–15+ years of experience in data, analytics, or insights, with at least 5–7 years in a senior leadership role (Director or VP level).
• Function Buildout: Proven track record of building and scaling a centralized analytics or data science function from the ground up, ideally in a mid-to-large-scale organization.
• Healthcare Domain: 5+ years of experience in the healthcare industry. Must have a deep understanding of clinical data, health-tech operations, and the regulatory environment (HIPAA, GDPR, etc.).
• Technical Ownership: Experience managing the full data stack, including collaboration with Engineering on data architecture, platform scalability, and analytics engineering (e.g., Snowflake, dbt, Databricks).
• Insights & Research Oversight: Demonstrated experience overseeing qualitative and quantitative research functions, specifically managing User Research (UXR) and Market Research teams to drive product/strategy decisions.
• AI/ML Implementation: Practical experience leading teams that have successfully deployed AI/Machine Learning models into production environments to solve business problems (e.g., predictive modeling for patient outcomes or operational efficiency).

Bonus points:

• Preferred: Master’s degree or PhD in Data Science, Health Informatics, MBA with a technical concentration, or a related quantitative field. An advanced degree is highly preferred given the "Innovation via AI" and "Insights/Research" components.
• Strategic Storytelling: Ability to translate complex data and AI concepts into compelling narratives for executive stakeholders and Board-level presentations.
• Platform Acumen: Strong familiarity with modern data stack (MDS) tools and "Platform-as-a-Product" thinking.