The Biostatistician/Epidemiologist is a key quantitative expert supporting impact analysis and outcome evaluations across complex programs using health data. This role involves applying advanced statistical techniques and epidemiological methods to rigorously assess program performance, generate insights from large-scale claims and clinical datasets, and bolster causal inference frameworks. Their analytical work directly informs program adjustments and performance monitoring, ensuring statistically valid and reliable outcomes across diverse populations and subgroups.
Responsibilities:
- Conduct advanced regression modeling, time-to-event analysis, hypothesis testing, and other statistical analyses to assess care delivery, cost outcomes, and population health impacts
- Provide statistical support for causal inference designs (e.g., Difference-in-Differences, Propensity Score Matching) by preparing data, conducting validations, and interpreting results
- Interpret complex statistical outputs in collaboration with Evaluation Leads, translating technical findings into clear, actionable insights for clients and stakeholders
- Generate comprehensive descriptive statistics and conduct comparative analyses of pre/post intervention periods and various cohorts
- Work within secure, cloud-based analytical environments (e.g., Snowflake, Databricks) to analyze large-scale healthcare claims data (e.g., from commercial payers, public health programs)
- Apply epidemiologic frameworks to evaluate the distribution, determinants, and outcomes of health conditions and interventions across populations
- Document all analytical assumptions, statistical significance thresholds, and test outcomes meticulously for auditability, reproducibility, and transparency
- Present statistical findings in stakeholder-ready formats, including clear tables, charts, graphs, and concise briefing decks for diverse audiences
- Coordinate closely with quality assurance teams to validate analytical assumptions, confirm statistical reproducibility, and ensure data integrity
- Assist in drafting technical appendices and methodology sections for evaluation reports and scientific publications
Experience Required:
- 6+ years of specialized experience in health services research, public health data analytics, or clinical research
- Proven ability to apply advanced statistical and epidemiological methods to real-world healthcare datasets
- Experience working with large-scale healthcare claims or clinical data
- Strong background in quantitative research design and analysis
Certifications / Education:
- Proficiency in statistical software such as SAS, R, or Python (with libraries like Pandas, NumPy, Scikit-learn, Statsmodels) (required)
- Master of Public Health (MPH) or Master of Science in Public Health (MSPH) with a concentration in Epidemiology, Biostatistics, or a related quantitative health field. A Ph.D. is often preferred
Skills:
- Statistical Modeling
- Hypothesis Testing
- Longitudinal Analysis
- Healthcare Data Analysis
- Epidemiological Methods
- R, Python, SAS
- Data Interpretation
- Causal Inference Support
- Scientific Communication
- Data Quality Assurance
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