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Senior Data Scientist, Fraud

Oscar Health

New York City, NY · HybridFull-time$164–215K/yrPosted 3 days agoStill listed 2 days ago

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At a glance

Compensation
$164–215K/yr
Location
New York City, NYHybrid
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Oscar Health is hiring a Senior Data Scientist, Fraud to shape its fraud data science capabilities and help uncover potential fraud and reduce avoidable medical costs. The role partners with Medical Economics and the Special Investigations Unit, manages projects end-to-end, and contributes to technical direction while mentoring junior data scientists. It is based in the New York City office with three in-office days per week.

Skills & qualifications

RequiredNice to have

Skills

SQL, requiredPython, requiredData Modeling, requiredAdvanced Analytics, requiredStatistical Modeling, requiredData Processing, requiredMachine Learning, requiredPredictive Modeling, requiredAnomaly Detection, requiredClustering, requiredGraph Analysis, requiredHealthcare Claims Analysis, nice to haveProvider Billing Analysis, nice to haveMedical Utilization Analysis, nice to havePharmacy Utilization Analysis, nice to have

Qualifications

4+ Years Data Science or Quantitative Technical Experience, required3+ Years SQL and Python Experience, required3+ Years Data Modeling Experience, requiredFraud Detection Experience, required

Benefits

Paid Time Off
Medical Insurance
Dental Insurance
Vision Insurance
Parental Leave
401(k) Match

Full job description

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 patterns, or medical and pharmacy utilization data.

This is an authentic Oscar Health job opportunity.

At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care -- an experience made whole by our unique backgrounds and perspectives.

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.

Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts.

Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant’s disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team ([email protected]) to make the need for an accommodation known.

California Residents: For information about our collection, use, and disclosure of applicants’ personal information as well as applicants’ rights over their personal information, please see our Privacy Policy.

How this job compares

Set against the 4,618 open Data Scientist jobs on Olive Jobs, counted November 10, 2026.

Pay
  • This posting$164–215K/yr
  • New York median$150–214K/yr357 salary ranges
  • US median$133–210K/yr3,652 salary ranges

This range's midpoint, $190K, is close to the New York median midpoint ($185K) — in the middle half of Data Scientist salary ranges in New York.

Openings
Olive Jobs lists 462 open Data Scientist jobs in New York and 4,618 across the US. 7% of them nationwide are listed as remote or flexible.
Hiring the most in New York
Experience
This posting asks for at least 4 years of experience; Data Scientist postings that state a minimum ask for 5 years at the median (4,010 postings).
Education
2,262 of the 4,618 open Data Scientist jobs (49%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 10, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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