Milliman’s Medicaid Finance and Policy Practice is seeking individuals to assist in providing analytical support for healthcare-related provider payment transformation engagements. Typical projects will include reimbursement methodology design, rate setting, and program funding strategies for all types of provider services, including hospital, physician and other practitioner, nursing facility, behavioral health, and home and community-based services. Related experience in healthcare is required.
Who We Are
Milliman’s Medicaid Finance and Policy Practice serves state Medicaid agencies and a wide variety of organizations significantly impacted by Medicaid reimbursement and funding, including hospital associations and safety net hospital systems. The practice is affiliated with the broader Milliman Medicaid Consulting Group consisting of 600+ professionals, including actuaries, healthcare consultants, attorneys, and statisticians.
Responsibilities
- Analyzing healthcare data, including:
- Claims datasets including services such as hospital, physician, and other medical services
- Service-related trend data
- Provider cost data
- Other publicly available data from sources such as the Bureau of Labor Statistics (BLS)
- Designing, developing, and using data models.
- Reviewing, evaluating, and summarizing data model output.
- Assisting with Medicaid policy research and analysis.
- Drafting technical documentation of work performed and related client reports and PowerPoint presentations.
- Reviewing the work of others to support Milliman’s quality control processes.
This position is designed for someone who wants to develop strong technical depth while keeping the door open to broader leadership opportunities. While the role will not initially include client-facing responsibilities, successful team members may have opportunities over time to manage projects, work directly with clients, mentor or manage colleagues, or pursue a combination of these paths.
Qualifications
- Bachelor’s Degree or higher.
- Minimum of 5 years of experience analyzing large data sets.
- Experience using database management and statistical programming tools, including SAS, SQL, or Python:
- Ability to write or learn SAS code without point-and-click user interfaces is required.
- Experience with SQL, Python, and/or Databricks is strongly preferred.
- Interest and aptitude for performing detail-oriented analytical work.
- Ability to effectively communicate technical information and concepts, both verbally and in writing.
- Ability to conduct and summarize research.
- Ability to use advanced Excel skills to perform data analysis is required. (Note that data visualization, such as creating PivotTables, is not a significant part of