Analyst, Payment Integrity (Data Mining)

Oscar Health
New York, New York, United StatesPosted 27 February 2026

Job Description

<p>Hi, we're Oscar. We're hiring an Analyst, Data Mining to join our Payment Integrity team.</p> <p>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.</p> <p><strong>About the role:</strong></p> <p>The Data Mining Analyst is responsible for reviewing claims data to identify incorrect payments. The analyst supports payment integrity quality control for incorrect payments identified both internally and by vendors.</p> <p>You will report into the Senior Manager, Payment Integrity</p> <p><strong>Work Location: </strong>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</p> <p><strong>Pay Transparency: </strong>The base pay for this role is: $28.26 - $37.10 per hour. You are also eligible for employee benefits and monthly vacation accrual at a rate of 15 days per year</p> <p><strong>Responsibilities:</strong></p> <ul> <li>Analyze and investigate claims data</li> <li>Support quality review claim and concept findings from internal and external partners regarding adverse claim outcomes.</li> <li>Utilize data analysis skills and tools to develop accurate, quantitative analyses of issues.</li> <li>Work with the team to identify thematic areas of opportunity to reduce incorrect payments.</li> <li>Mediate errors with key stakeholders</li> <li>Compliance with all applicable laws and regulations</li> <li>Other duties as assigned</li> </ul> <p><strong>Requirements:</strong></p> <ul> <li>2+ years of experience in healthcare</li> <li>2+ years of experience working with large claims data sets using excel or a database language</li> </ul> <p><strong>Bonus points:</strong></p> <ul> <li>Some coding experience or database language exposure</li> <li>2+ years of related work experience in payment integrity data mining </li> <li>Experience using SQL</li> </ul><div class="content-conclusion"><p><span style="font-weight: 400;">This is an authentic Oscar Health job opportunity. Learn more about how you can safeguard yourself from recruitment fraud</span><a href="http://hioscar.com/careers/recruitment-fraud-alert"><span style="font-weight: 400;"> </span><span style="font-weight: 400;">here</span></a><span style="font-weight: 400;">. </span></p> <p><span style="font-weight: 400;">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.</span></p> <p><strong>Pay Transparency: </strong><span style="font-weight: 400;">Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. </span><span style="font-weight: 400;">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.</span></p> <p><span style="font-weight: 400;"><strong>Artificial Intelligence (AI): </strong>Our <a href="http://hioscar.com/careers/ai-guidelines" target="_blank">AI Guidelines</a> outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts.</span></p> <p><strong>Reasonable Accommodation: </strong><span style="font-weight: 400;">Oscar applicants are considered solely based on their qualifications, without regard to appl ... (truncated, view full listing at source)