Hyderabad, Telangana, India
Live, first seen by us 66 days agoWork setup in the employer’s posting: HybridFrom the employer’s posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Lead exploratory analysis of claims paid data to find overpayments and anomalies
Reverse engineer claims outcomes to find root causes of payment issues
Apply CMS rules and contract knowledge to guide data mining investigations
Turn claims insights into use cases and solution ideas for analytics and product teams
Support refinement and scaling of claims monitoring and overpayment detection
Lead exploratory analysis of claims paid data to identify utilization patterns, anomalies, and potential overpaid or inappropriate claims
Perform reverse engineering of claims outcomes to understand root causes of payment issues and system behaviors
Apply deep knowledge of CMS rules, contract interpretation, reimbursement, and workflows to guide data mining and investigative efforts
Translate operational and claims insights into clear use cases, concepts, and solution ideas for analytics and product teams
Support ongoing refinement and scaling of claims monitoring and overpayment detection capabilities
7+ years of experience in US healthcare claims with a strong focus on claims adjudication and Data Mining payment Integrity
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Day 66
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From 10,789 similar postings that came down, and 243 of EXL Service’s. Coming down is not always a hire.
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New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
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We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Extensive experience across Medicare, Medicaid or commercial business
• Demonstrated expertise in 360-degree claims review, auditing, and payment integrity
• Proven ability to identify patterns, anomalies, and inappropriate payments within large claims datasets
• Strong analytical mindset with the ability to bridge operations and data science
• Experience collaborating with cross-functional teams (analytics, product, strategy, compliance)
• Excellent communication skills with the ability to explain complex claims concepts clearly
• Prior involvement in payment integrity data mining or recovery initiatives
• Experience supporting or designing claims analytics or data mining non-clinical programs
Key Responsibilities
• Lead exploratory analysis of claims paid data to identify utilization patterns, anomalies, and potential overpaid or inappropriate claims
• Apply deep knowledge of CMS rules, contract interpretation, reimbursement, and workflows to guide data mining and investigative efforts
• Perform reverse engineering of claims outcomes to understand root causes of payment issues and system behaviors
• Translate operational and claims insights into clear use cases, concepts, and solution ideas for analytics and product teams
• Partner closely with analytics, product, and strategy teams to ensure solutions align with real-world claims operations
• Validate data-driven findings against practical claims and payment realities
• Clearly communicate insights, risks, and opportunities to both technical and non-technical stakeholders
• Support ongoing refinement and scaling of claims monitoring and overpayment detection capabilities
Required Qualifications
• 7+ years of experience in US healthcare claims with a strong focus on claims adjudication and Data Mining payment Integrity
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Hyderabad, Telangana, India
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