Data Scientist Principal, AI Development and Governance

This is a fully remote, full-time senior individual-contributor role focused on building trustworthy AI and machine learning capabilities for healthcare fraud, waste, and abuse detection.
You’ll split your time between developing production-ready models and establishing the standards that guide responsible AI across the broader data science team.
The role combines hands-on machine learning, generative AI evaluation, model governance, and large-scale healthcare data analysis.
You’ll work with complex claims data to develop findings that can be trusted by healthcare partners, investigators, and auditors.
The position also requires the ability to assess emerging AI capabilities, determine where they can add value, and identify situations where they are not yet appropriate.
You’ll collaborate with data scientists, BI developers, subject matter experts, partners, and auditors across a distributed U.S. team.
This opportunity is well suited to an experienced data scientist who enjoys both technical delivery and setting rigorous standards for responsible AI.

• Master’s degree in statistics, computer science, engineering, applied mathematics, economics, or another quantitative discipline, or a bachelor’s degree in a related quantitative field combined with equivalent hands-on experience.
• 8+ years of experience building, validating, and deploying machine learning models using real-world data, including experience establishing technical standards for other data scientists.
• Strong working knowledge of responsible AI and model-risk practices, including model documentation, monitoring, bias and drift detection, validation, and production governance.
• Demonstrated experience evaluating generative AI and LLM use cases for both technical feasibility and risk, including the ability to determine when an LLM should not yet be used for a particular application.
• Strong Python and SQL skills, including experience performing feature engineering and analytical work within very large-scale data warehouses.
• At least 2 years of experience working with healthcare claims data, including Medicare, Medicaid, or commercial claims, together with working knowledge of medical terminology and coding systems such as ICD-10, CPT, HCPCS, and DRG.
• Experience presenting technical methodologies, model results, and governance decisions to clients, partners, auditors, or other stakeholders, with the ability to adapt explanations to both technical and non-technical audiences.
• Strong analytical and critical-thinking skills, with the ability to assess complex AI systems, identify risks, and establish practical standards for responsible deployment.
• Prior experience in a formal model-risk or responsible-AI role is desirable, including experience outside the healthcare sector.
• Experience with graph or network analytics, entity resolution, or record linkage is an advantage.
• Experience piloting generative AI tools in regulated or high-scrutiny environments is preferred.
• Experience with AWS and/or Snowflake environments, including Snowpark or model lifecycle tooling, is beneficial.
• Familiarity with payer coverage policies such as LCDs, NCDs, private carrier policies, and industry claim edits such as NCCI is a plus.
• No U.S. citizenship requirement and no security clearance is required for this position.