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Director, Data Science - Risk Adjustment

Oscar Health

Role at a glance

Category
Risk
Work arrangement
On-site
Location
New York, NY
Salary range
$218,592 to $286,902
Posted
Jun 13, 2026
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Oscar Health is hiring a Director, Data Science - Risk Adjustment in New York, NY. This is a Risk role in the governance, risk, and compliance field, with a posted range of $218,592 to $286,902. Review the full details below and apply directly with Oscar Health.

Hi, we re Oscar. We re hiring a Director, Data Science - Risk Adjustment 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 Director, Data Science Risk Adjustment, leads teams developing advanced analytics, machine learning, and AI-driven solutions that support Oscar’s risk adjustment strategy and broader business objectives. This leader partners cross-functionally across Data Science, Product, Engineering, Clinical, Finance, and Actuarial organizations to build scalable analytical systems, drive operational and financial performance, and deliver high-impact insights in complex healthcare environments. The role combines organizational leadership, technical depth, and strategic influence, requiring strong experience in healthcare analytics, statistical modeling, experimentation, and modern AI/LLM-enabled workflows. You will report into the VP, Data. Work Location: This position is based in either our New York City office, Los Angeles office, Tempe Office, or can sit remotely in San Fransisco, Boston, Dallas, or Atlanta markets. If you live in the NYC, LA, or Tempe markets, this will be 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. # -Hybrid Pay Transparency: The base pay for this role is: $218,592 - $286,902 per year. You are also eligible for employee benefits, participation in Oscar s unlimited vacation program, company equity grants, and annual performance bonuses. Responsibilities: Translates company goals into roadmaps, plans, and tactics for their area. Key part of the department leadership team to influence in team strategy, operations, scope and culture Leads and manages medium sized team(s) of data scientists and/or analysts, including managers Influences and collaborates closely with senior data and business leaders across multiple areas Leads team(s) that research, develop, and maintain data pipelines, statistical/ML models, and/or advanced analyses Lead delivery of solutions through organizational design, cross-functional advocacy, systems design, management, and/or mentorship. Champion a culture of collaboration

Full responsibilities and requirements are on Oscar Health's application page.

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About Oscar Health
Hiring for governance, risk, and compliance roles on GRC Careers.
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Location and market context

This role is based in New York, NY on-site. Local candidates benefit from being close to Oscar Health's teams and regional hiring market. Confirm the exact in-office expectation and any relocation support with the employer.

About risk management roles

Risk roles own the methodology for identifying, assessing, and escalating enterprise, operational, and technology risk. Second-line teams set risk appetite and challenge the first line. Roles like this one are typically evaluated against frameworks such as enterprise and operational risk frameworks, NIST AI RMF, and risk-appetite and escalation practices.

How to position yourself for this risk management role

Strong candidates emphasize risk assessment methodology, appetite and escalation, cross-functional partnership, and clear reporting to senior leadership and the board. In your resume and outreach, tie your experience to how Oscar Health would apply enterprise and operational risk frameworks, NIST AI RMF, and risk-appetite and escalation practices, and lead with concrete outcomes rather than duties.

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