RHTP Research Data Scientist

State of Montana • Great Falls, VA

21h • Hybrid

About The Position

The Montana Department of Public Health and Human Services (DPHHS) has a career opportunity within the Rural Health Transformation Program. The Research Data Scientist is the advances analytics and evaluation lead for the Rural Health Transformation Program (RHTP) and serves as a key member of Montana’s rural health analytics community of practice. This position applies rigorous statistical and quantitative methods to evaluate rural health systems, forecast future needs, and inform strategic decision-making. The data scientist develops predictive models, leads evaluations of RHTP initiatives, and produces policy-relevant insights on access, quality, cost, workforce, and sustainability that guide program implementation, funding decisions, and policy recommendations. The role ensures that Montana meets and exceeds the data and evaluation requirements established by the Centers for Medicare & Medicaid Services (CMS) for the Rural health Transformation Program. This position operates within a federated analytics model, collaborating closely with the Department’s central analytics tam and Data Management Office to apply shared methods, metrics, and tools white addressing RHTP-specific anlytic needs. The incumbent participates in department-wide analytics communities of practice, helping promote reproducible research methods, reduce duplication, and build statewide capacity for rural health analytics. Our mission at DPHHS is serving Montanans in their communities to improve health, safety, well-being, and empower independence. By joining the RHTP team, you’ll help shape the future of rural health care in Montana. These positions offer impactful work improving access and equity for rural communities, competitive salaries and benefits (including health coverage, retirement plans, paid leave, and eligibility for Public Service Loan Forgiveness), hybrid work options, and opportunities to collaborate statewide.

Requirements

• Knowledge of health care financing concepts such as reimbursement methodologies, value-bases payment, hospital and clinic cost structures, and public sector budgeting or fiscal processes.
• Ability to translate technical analytic results into concise, accessible narratives and recommendations for decision-makers.
• Ability to work collaboratively with interdisciplinary teams and external partners, including rural and tribal stakeholders, and to facilitate meetings and workgroups.
• Master's degree in computer science, Mathematics, Statistics, Economics, Data Science, Public Health or related field.
• Three years of progressively responsible, job-related work experience in quantitative analysis, statistical modeling, predictive analytics, or program evaluation in a health insurance, hospital/healthcare, consulting, governmental or similar setting.
• Other combinations of directly related education and experience may be considered on a case-by-case basis.

Nice To Haves

• Experience building and validating predictive models or risk scores in a health care context, including performance metrics such as AUC, calibration, and fairness/equity checks across subpopulations (e.g., rural vs urban, tribal vs non-tribal).
• Experience with health care claims data (e.g., Medicare, Medicaid, commercial) and knowledge of common coding systems (e.g., ICD, CPT, HCPCS, DRG).
• Experience working within or with state agencies, health systems, or health plans on payment models, delivery system reform, or rural health initiatives.

Benefits

• competitive salaries and benefits (including health coverage, retirement plans, paid leave, and eligibility for Public Service Loan Forgiveness)
• hybrid work options
• opportunities to collaborate statewide

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level