Senior Data Scientist, Fraud

Hi, we're Oscar. We're hiring a Senior Data Scientist, Fraud to join our Data Team.

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 patterns, or medical and pharmacy utilization data.

Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements.