Senior Biostatistician
$150,000–$182,500 year
HybridConshohocken, Pennsylvania, United States
Job Summary
Develop and apply statistical and machine-learning models to high-dimensional data to support biomarker strategy and clinical evidence generation. Work with multi-omic profiling, PK/PD biomarkers, and biobank- or EHR-linked genomic data to inform translational strategy. Generate real-world evidence from observational data using causal-inference methods and support the design and analysis of clinical trials and real-world data studies. Contribute to protocol development, statistical analysis plans, and publications across translational science and early clinical research. This individual contributor role reports to the VP of Biostatistics and focuses on early development (Phase IIa) and causal inference using real-world data.
Required Qualifications
- Ph.D. in (Bio)statistics, Statistics, Data Science, or a related quantitative field
- At least 2 years of relevant experience (or equivalent internship, co-op, or postdoctoral research)
- Proficiency in R and SAS
- Working knowledge of Python and machine-learning libraries (scikit-learn, PyTorch, TensorFlow)
- Ability to communicate complex analyses to non-statisticians and influence decisions across scientific and clinical teams
- Experience with real-world data sources
- Knowledge of regulatory guidelines
Desired Qualifications
- Between 3-5 years of relevant work experience
- Ability to apply human genetics methods (e.g., GWAS, polygenic risk scores, sequencing) to inform translational strategy
- Building data pipelines that transform high-dimensional and real-world datasets into analysis-ready form
- Familiarity with multi-omic and PK/PD biomarker data and with biobank- or EHR-linked genomic datasets
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