Key Responsibilities

Run structured literature searches on questions that matter to Solace's strategic direction and maintain a working literature library the CMO can pull from
Synthesize the published evidence base honestly — what the literature does and doesn't support — into briefings useful to leadership conversations
Construct cohorts and execute analyses inside the CMS Virtual Research Data Center (VRDC) on Medicare claims data, working from analytic specs designed by senior researchers and the Head of Impact Analytics
Build and maintain analytical datasets and code with attention to data quality, integrity, and reproducibility
Translate VRDC output into findings the research team can review, iterate on, and use downstream
Document analytic work to a standard that supports team-wide reproducibility and review
Partner with senior researchers, clinical, and operations stakeholders on shaping research questions worth pursuing
Contribute to white papers, case studies, and (over time) peer-reviewed publications, in supporting and co-author roles

Requirements

Master's-level training in Public Health (HSR or Biostatistics concentration), Health Services Research, Health Policy with quantitative concentration, Epidemiology, Biostatistics, or a closely related field
Approximately 1-3 years of post-graduate experience working with healthcare data; structured research-assistant work during graduate training counts toward this
Zotero for organizing literature
PubMed search syntax — Boolean operators, MeSH terms, filters
SQL for complex querying and data manipulation
R or Python for statistical analysis and research computing
Structured literature search, screening, and evidence-synthesis methods
Notion (or a comparable structured knowledge-management platform) for collaborative documentation and library-building
Healthcare claims data structures, particularly Medicare RIF/LDS files
Cohort construction and longitudinal analysis methods relevant to claims data
Descriptive epidemiology and standard regression techniques for observational data
Healthcare data standards (ICD-10, HCPCS, NDC, DRG codes) and Medicare/commercial insurance structures
Quasi-experimental and causal-inference methods relevant to claims-based outcomes research (propensity score matching, difference-in-differences, survival analysis)
Reproducible-analysis practices and version control (git)
VRDC operational conventions (cell-size suppression, output-review caps, named-seat constraints) — or willingness to ramp on these quickly
High standards for defensible research and willingness to be honest about what the data can and cannot support
Business sense and the ability to deliver on non-academic timelines while making pragmatic research choices
Strong written communication, with the ability to write clearly for both technical and executive audiences
Attention to detail in code, documentation, and results
Comfort working across two stakeholders with different priorities, and the judgment to be honest about capacity when they pull in different directions
Natural curiosity that extends beyond a narrow specialty

Preferred Qualifications

Hands-on experience with Medicare claims data specifically (rather than commercial claims only)
Prior work under a CMS DUA or in a CMS Innovator-licensed environment
A peer-reviewed or working-paper first or co-author publication based on original work
Prior work in health tech, digital health, or startup environments