Healthcare Outcomes Research Analyst – Business Information Consultant

Elevance Health

. Design and conduct retrospective observational studies evaluating the clinical and financial impact of healthcare and pharmacy programs.

Posted 11/9/2026full-timeUnited StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and conducting observational studies in healthcare, utilizing advanced statistical methodologies such as Propensity Score Matching and Regression Analysis. Proficient in analyzing complex healthcare datasets and translating findings into actionable insights for stakeholders.

Highest-signal resume keywords

Python ProgrammingR ProgrammingSAS ProgrammingHealth Economics and Outcomes Research (HEOR)Predictive Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Propensity Score MatchingDifference-In-DifferencesRegression AnalysisRisk AdjustmentData ValidationStatistical TestingSensitivity AnalysesLongitudinal AnalysisCausal Inference MethodologiesStatistical Program Development

Soft Skills

CollaborationCommunicationAnalytical ThinkingProblem SolvingPresentation Skills

Tools & Technologies

Healthcare DatasetsStatistical SoftwareDatabasesDecision-Support Tools

Industry Keywords

Healthcare UtilizationPharmacy ClaimsReal-World Evidence (RWE)Managed CarePharmacy Benefit Management (PBM)

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design and conduct retrospective observational studies evaluating the clinical and financial impact of healthcare and pharmacy programs.
Apply propensity score matching, difference-in-differences, regression analysis, and risk adjustment to assess program effectiveness, utilization, and outcomes.
Develop analytical study designs covering study populations, comparison groups, baseline and follow-up periods, outcome measures, and statistical approaches.
Extract, integrate, manipulate, and analyze large and complex healthcare datasets.
Develop, modify, and maintain statistical programs using Python, R, and/or SAS, with emphasis on transitioning workflows to Python and R.
Conduct data validation, statistical testing, and sensitivity analyses.
Analyze healthcare utilization, medical and pharmacy costs, and clinical outcomes.
Collaborate with clinical, pharmacy, and business stakeholders to translate business questions into actionable insights.
Develop research summaries, presentations, and reports for internal leadership, external clients, and stakeholders.
Support advanced analytics initiatives, including predictive modeling.
Create and maintain databases tracking business performance.
Analyze data and summarize performance using summary statistical procedures.
Develop and analyze business performance reports and document deviations and anomalies.
Create and publish periodic and ad hoc reports.
Manage business issues and develop diagnostic or tracking data for decision-support tools.

Requirements

What you’ll need

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.
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.
Candidates must reside within a reasonable commuting distance from one of the posting locations unless an accommodation is granted as required by law.
Python, R, and/or SAS programming experience.
Experience with large-scale medical claims, pharmacy claims, and member eligibility datasets.
Knowledge of propensity score matching, difference-in-differences, regression modeling, and risk adjustment.
Experience conducting data validation, statistical testing, and sensitivity analyses.

Benefits

Comp & perks

Merit increases
Paid holidays
Paid Time Off
Incentive bonus programs
Medical benefits
Dental benefits
Vision benefits
Short-term disability benefits
Long-term disability benefits
401(k) + match
Stock purchase plan
Life insurance
Wellness programs
Financial education resources
Hybrid work flexibility
Professional and personal growth opportunities