In this role of Healthcare Statistical Data Scientist, you will support the development of analytical models to identify payment anomalies in client healthcare claims data (fraud, waste, or abuse). The results from your work will be reviewed by clinical analysts for outcome success. To be successful in this role, you will have foundational knowledge of statistical models, data mining, and machine learning, as well as a growing ability to combine analytical skills with business context in a healthcare setting.
Responsibilities
- Support the research and development of analytical models for new and ongoing product lines under the guidance of senior data scientists.
- Apply ML techniques including gradient boosting, NLP, and probabilistic modeling, with guidance on approach selection and implementation.
- Assist in developing and training machine-learning models for use cases such as claims cost prediction, fraud and abuse detection, and provider performance analysis.
- Contribute to ongoing monitoring of product lines, including tracking success metrics to support executive decision-making.
- Develop understanding of key organizational initiatives and contribute analytical work that supports actionable recommendations.
- Analyze and interpret medical, pharmacy, and dental claims data (CPT/HCPCS, ICD-10, DRG, NDC) with growing independence.
- Translate domain knowledge into features and model strategies with direction from senior team members.
- Collaborate with clinicians, product managers, and business stakeholders to understand problem definitions and measurement approaches.
- Communicate analytical findings clearly to team members and stakeholders, with support on complex or executive-facing deliverables.
- 2+ years of experience in healthcare analytics or a related analytical role; equivalent academic project experience considered.
- Foundational exposure to statistical, analytical, or data mining techniques and a demonstrated ability to apply them in a business context.
- Proficiency in Python and SQL programming required.
- Basic understanding of healthcare claims, adjudication, and claims content; willingness to deepen knowledge on the job.
- Familiarity with healthcare data and common analytics terminology (ICD, CPT, REV, DRG, etc.) preferred.
- Demonstrated ability to solve problems with moderate direction and escalate appropriately when needed.