Healthcare Outcomes Research Analyst (Business Information Consultant)

Location: This role requires associates to be in-office 1 day per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Ideal candidates will be able to report to one of our Pulse Point locations in Atlanta, GA, Tampa, Florida, Grand Prairie, TX, Indianapolis, IN or Mason, OH. Alternate locations may be considered if candidates reside within a commuting distance from an office. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. The Healthcare Outcomes Research Analyst (Business Information Consultant) is responsible for conducting healthcare data analyses and retrospective observational studies to evaluate clinical and pharmacy programs, healthcare utilization, and total cost of care. The analyst will apply statistical and observational research methodologies, including propensity score matching (PSM), difference-in-differences (DiD), regression modeling, and risk adjustment, to evaluate program effectiveness and healthcare outcomes.

How you will make an impact: Designs and conducts retrospective observational studies to evaluate the clinical and financial impact of healthcare and pharmacy programs using large-scale medical and pharmacy claims data. Applies advanced statistical methodologies, including propensity score matching (PSM), difference-in-differences (DiD), regression analysis, and risk adjustment, to assess program effectiveness, healthcare utilization, and outcomes. Develops appropriate analytical study designs, including identification of study populations, comparison groups, baseline and follow-up periods, outcome measures, and statistical approaches. Extracts, integrates, manipulates, and analyzes large and complex healthcare datasets, including medical claims, pharmacy claims, and member eligibility data. Develops, modifies, and maintains statistical programs using Python, R, and/or SAS, with an emphasis on transitioning analytical workflows to Python and R.Conducts data validation, statistical testing, and sensitivity analyses to ensure accuracy, reliability, and appropriate interpretation of analytical findings. Analyzes healthcare utilization, medical and pharmacy costs, and clinical outcomes to evaluate program performance and identify opportunities for improvement. Collaborates with clinical, pharmacy, and business stakeholders to translate business questions into analytical approaches and actionable insights. Develops research summaries, presentations, and reports to communicate study methodologies, findings, and recommendations to internal leadership, external clients, and other stakeholders. Supports additional advanced analytics initiatives, including predictive modeling, as business needs evolve. Creates and maintains databases to track business performance. Analyzes data and summarizes performance using summary statistical procedures. Develops and analyzes business performance reports (e.g. for claims data, provider data, utilization data) and provides notations of performance deviations and anomalies. Creates and publishes periodic reports, as well as any necessary ad hoc reports. Manages business issues and devises best way to develop appropriate diagnostic and/or tracking data that will translate business requirements into usable decision support tools.

Minimum Requirements: Requires a BS/BA degree in related field and a minimum of 5 years experience; or any combination of education and experience which would provide an equivalent background. Preferred Skills, Capabilities and Experiences: Experience working with medical and/or pharmacy claims data, including longitudinal analyses of healthcare utilization and costs highly preferred. Experience in health economics and outcomes research (HEOR), real-world evidence (RWE), or healthcare program evaluation highly preferred. Experience with additional causal inference methodologies, including inverse probability weighting, interrupted time series, or other quasi-experimental methods highly preferred. Experience with predictive modeling or machine learning techniques highly preferred. Familiarity with healthcare payer, pharmacy benefit management (PBM), or managed care environments highly preferred. Master's degree in Statistics, Biostatistics, Epidemiology, Health Economics, Data Science, Public Health, or a related quantitative discipline preferred.

Job Level: Non-Management Exempt