Postdoctoral Fellow, Epidemiology & Oncology RWE
AstraZeneca
Full-time
Remote friendly (Waltham, MA)
United States
Clinical Research and Development
Want to see how your resume matches up to this job? A free trial of our JobsAI will help! With over 2,000 biopharma executives loving it, we think you will too! Try it now — JobsAI.
Role Summary
Do you have expertise in, and a passion for, the development and application of advanced epidemiology methods to ensure rigorous insights for patients? Would you like to apply your expertise to impact early and late oncology clinical development in an organization that follows the science and turns ideas into life-changing medicines?
Responsibilities
- Design and implement demonstration projects to test approaches that correct or minimize biases in claims, electronic health records, and multi-modal data.
- Compare results from these methods to AZ's status-quo analytic approaches and validate against historical clinical trials' standard-of-care arms.
- Collaborate with epidemiologists and data scientists to drive innovative research within AstraZeneca’s Oncology portfolio.
Qualifications
- PhD in Epidemiology, Pharmacoepidemiology, Biostatistics, Statistical Genetics, Clinical Informatics, Computer Science, Health Informatics, or related fields.
- Essential: Solid understanding of epidemiological study design; experience with Real World Data (claims, EHRs) or clinical trial data; significant experience with bias and bias-correction methods (e.g., propensity score weighting/matching, instrumental variable analysis, matching adjusted indirect comparisons); familiarity with generalizability/transportability; experience coding in R or similar.
- Desirable: Oncology experience; understanding of drug development; experience in causal inference, Bayesian methods, and/or quantitative bias analysis; pharma/clinical trials/regulator engagement.
Skills
- Solid understanding of epidemiological study design
- Experience with Real World Data or clinical trial data
- Bias correction methods expertise (propensity scores, IV analysis, etc.)
- Generalizability and transportability approaches
- Proficiency in R (or similar)
Education
- PhD in Epidemiology, Pharmacoepidemiology, Biostatistics, Statistical Genetics, Clinical Informatics, Computer Science, Health Informatics, or related field
Additional Requirements
- Collaborative, innovative, curious mindset; commitment to patient-focused research.