Jobs / United States / Oscar Health

Oscar Health

Senior Data Scientist, Fraud

New York, New York, United States Posted today $163,944 - $215,176 per year

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Product managementData engineeringMachine learningComplianceSQLPythonStatisticsPharmacy

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Sponsorship verdict

No sponsorship evidence yet

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  • No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
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  • Confirmed live todayWhen a source last listed this job as open.
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No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

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About the role

Hi, we're Oscar. We're hiring a Senior Data Scientist, Fraud to join our Data 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: Oscar's data team is focused on pushing our understanding of the complex landscape of the healthcare and insurance business. Insurance companies sit on a trove of data that is both broad and deep—spanning financial claims, clinical medical records, and rich product interaction data from our members. The Senior Data Scientist, Fraud will help shape Oscar’s fraud data science capabilities and partner with the Medical Economics team and Special Investigations Unit (SIU) to turn Oscar’s data into investigative leads and tools that uncover potential fraud and reduce avoidable medical costs. As a Senior Data Scientist on this team, you will partner closely with stakeholders to understand business challenges and identify opportunities for data science to drive impact. You will independently manage stakeholder relationships for your projects, translate business needs into technical solutions, and contribute to the fraud data science roadmap. You will own projects end-to-end—scoping problems with stakeholders, designing the technical approach, implementing pipelines and models, validating outputs, and iterating after launch. Beyond individual projects, you will contribute to the team’s technical direction and mentor junior data scientists. You will report to the Director, Data Science. Work Location: This position is 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 to suit your schedule. #LI-Hybrid Pay Transparency: The base pay for this role is: $163,944 - $215,176 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants and annual performance bonuses. Responsibilities: • Design, build, and maintain data pipelines, machine learning models, and analytical tools supporting Oscar’s fraud detection and prevention efforts. • Partner closely with SIU and Medical Economics to understand business needs, translate them into data science solutions, and independently manage stakeholder relationships for your projects. • Own projects end-to-end, including problem definition, technical design, implementation, validation, and ongoing evaluation and improvement. • Interact and collaborate closely with data and business counterparts across functional areas • Work with your team and manager to identify opportunities and contribute to the fraud data science roadmap and longer-term technical direction. • Provide mentorship and technical guidance to junior data scientists. • Compliance with all applicable laws and regulations. • Other duties as assigned. Requirements: • 4+ years of experience in data science or another quantitative technical field, which may include academia. • 3+ years of experience using SQL and Python to query, manipulate, and analyze data. • 3+ years experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing. • Experience applying supervised or unsupervised machine learning techniques, such as predictive modeling, anomaly detection, clustering, or graph/network analysis, to identify potential fraud in healthcare, insurance, financial services, or other industries. Bonus points: • Experience analyzing healthcare claims, provider billing pat

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