Note: The job is a remote job and is open to candidates in USA. GDIT is a technology and professional services company delivering technology solutions and mission services to government, defense, and intelligence organizations. The Data Scientist Principal will build and deploy healthcare fraud, waste, and abuse models while establishing responsible AI, generative AI, validation, monitoring, and model-risk standards. The role also involves reviewing models, advising on AI use cases, and presenting methodologies and controls to partners, clients, and auditors.
Responsibilities
- Set the modeling and validation standards the Data Science team works against; how models get documented, monitored, and checked for drift and bias. You'll review the team's models against that bar before they go to production and recommend what must change first
- Write and maintain the program's responsible-AI and GenAI policy. The harder half is generative AI inside the FWA pipeline itself, like case narrative summarization or investigator-facing drafts, where a weak output lands in front of an investigator. Internal tooling such as code assistants needs a policy too, and it's the easier one to write
- Build and ship FWA models yourself. Supervised risk scoring against the claims warehouse, feature engineering at claim-record scale, and validation under heavy class imbalance and fraud schemes that shift faster than confirmation arrives
- Walk HFPP Partners and internal auditors through how a given model or AI-assisted step works, including validation results and controls. Expect to defend methodology choices to people whose job is finding the gaps in them
- Decide what's worth piloting as generative AI capability shifts and say no to what isn't ready for a healthcare FWA context yet
- Work across a multi-disciplinary team of Data Scientists, BI Developers, and FWA Subject Matter Experts (100% remote, distributed across the US). Governance questions come to you regardless of which sub-team raised them
Skills
- AI Governance, Artificial Intelligence (AI), Generative AI
- 5 + years of related experience
- No
- Master's degree in a quantitative field (statistics, computer science, engineering, applied mathematics, economics, or related), or a Bachelor's in one of those fields with equivalent hands-on experience
- 8+ years building, validating, and deploying ML models on real-world data, including a track record of setting technical standards that other data scientists work against
- Working knowledge of responsible-AI and model-risk practice: documentation, monitoring, bias and drift detection, and what production-ready governance looks like for a model whose output drives decisions about providers
- Experience evaluating generative AI and LLM use cases for both feasibility and risk, including cases where your answer was that an LLM shouldn't be used yet
- Competence in Python and SQL, including feature engineering inside a data warehouse at very large scale
- 2+ years working with healthcare claims data (Medicare, Medicaid, or commercial), plus working knowledge of medical terminology and healthcare coding systems (ICD-10, CPT, HCPCS, DRG)
- Experience presenting technical and governance decisions to clients, partners, or auditors. You should be able to defend a methodology choice to a technical reviewer and explain that same decision to someone who isn't one
- United States
- Full time
- 40
- Less than 10%
- Remote
- Any Location / Remote
- Prior experience in a formal model-risk or responsible-AI role, even outside healthcare
- Graph or network analytics, entity resolution, or record linkage
- Experience piloting generative AI tools in a regulated or high-scrutiny setting
- AWS and/or Snowflake environments, including Snowpark or model lifecycle tooling
- Experience with payer coverage policy (LCDs, NCDs, private carrier policies) and industry claim edits (NCCI)
Benefits
- AI-powered career tool that identifies career steps and learning opportunities.
- An internal mobility team focused on helping you achieve your career goals.
- Comprehensive benefits and wellness packages.
- 401K with company match.
- Paid time off.
- Full-flex work week to own your priorities at work and at home.
- Award-winning culture of innovation and a military-friendly workplace.
- Medical plan options, some with Health Savings Accounts.
- Dental plan options.
- A vision plan.
- A 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match.
- A variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave.
- 15 days of paid leave per calendar year for vacations, personal business, and illness.
- 10 paid holidays per year.
- Up to 160 hours of paid leave in a rolling 12 month period through the GDIT Paid Family Leave program for eligible employees.
- Short- and long-term disability benefits.
- Life insurance.
- Accidental death and dismemberment insurance.
- Personal accident insurance.
- Critical illness insurance.
- Business travel and accident insurance.
- Full-flex work weeks where possible.
- Remote work.
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