Healthcare Statistical Data Scientist

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.
• Aid in developing and training machine-learning models for use cases such as claims cost prediction, fraud and abuse detection, and provider performance analysis.
• Ongoing monitoring of product lines, including tracking success metrics to support executive decision-making.
• Contribute to 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.

Qualifications

• 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.