Wisconsin DHS-Embedded Data Scientist I

The Institute for Research on Poverty (IRP) seeks a Data Scientist who will serve as a data expert for Medicaid health policy research in the Medicaid Evaluation and Research (MER) operational area at IRP. The position will work closely with DMS to prepare DMS data for evaluation and policy analysis and will support complex data projects and policy initiatives for Wisconsin's Medicaid and FoodShare programs. Working alongside DMS staff and contracted Medicaid Management Information System (MMIS) vendors, this role is responsible for the end-to-end lifecycle of data analysis and reporting-from gathering requirements with stakeholders to the technical development and analysis of ad hoc and standard reports. The ideal candidate bridges the gap between policy research and technology, ensuring all data outputs further Medicaid and Foodshare operations and implementation.

We aim to hire Data Scientists with expertise and experience with Medicaid claims data. When you join our team, you're not just bringing your expertise. We are committed to fostering your professional development goals and supporting your career advancement through continued learning opportunities.

This role is currently eligible for remote work. Continued remote work eligibility will follow University of Wisconsin-Madison policies and any future updates. Also this position requires reliable transportation for occasional onsite work if needed.

Key Job Responsibilities

• Develop expertise in the content, structure, and idiosyncrasies of Medicaid/ FoodShare data by understanding the origin and interpretation of variables, as well as learning about policy issues related to the data
• Prepares data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources
• Documents approaches to address research questions
• Review and analyze changes in federal and state regulations for impact on Medicaid/Foodshare policy and processes, especially those necessary for data collection and reporting. Implement necessary revisions to reporting frameworks to ensure compliance with shifting regulations
• Implements appropriate data science techniques under the guidance of other data scientists, statisticians, and/or other researchers to find data patterns and answer research questions chosen by the lead researcher including data visualization, statistical analysis, machine learning, and data mining
• Organizes and automates project steps for data preparation and analysis
• Composes and assembles reproducible workflows and reports to clearly articulate patterns to researchers and/or administrators