The Applied Statistics Staff Scientist will play a key role in advancing data-driven research at a leading computational sciences institute. This position supports multiple concurrent projects by implementing rigorous statistical frameworks to interpret high-dimensional molecular and cellular biology datasets.
Key Responsibilities
- Partner with interdisciplinary research teams to design and execute statistical strategies for integrating and interpreting complex biological data.
- Apply formal inference techniques, including hypothesis testing, model selection, uncertainty quantification, and power analysis, to support robust scientific conclusions.
- Construct and validate statistical models tailored to diverse data types—such as genomic, epigenomic, single-cell, and multi-omics datasets—using generalized linear models, hierarchical modeling, and other appropriate methods.
- Ensure analytical reproducibility through version-controlled workflows, thorough documentation, and peer-reviewed coding practices.
- Contribute to the dissemination of research by preparing data, code, and visualizations for publication and broader scientific use.
- Remain current with emerging methodologies in statistical bioinformatics and computational biology to inform best practices across projects.
Qualifications
A bachelor’s degree plus at least one year of relevant experience—or an equivalent combination of education and practical training—is required. Candidates must show a solid foundation in statistical theory and applied inference, including probability, linear modeling, resampling methods, and study design. Experience handling complex biological datasets is essential, with familiarity in addressing common challenges such as batch effects, sparsity, and confounding variables.
Strong technical skills in R or Python are expected, along with a demonstrated ability to create clear, publication-ready figures and tables. Applicants should also exhibit strong written communication, collaboration skills, and a commitment to ethical research practices.
Preferred Background
- Advanced degree in Statistics, Biostatistics, Data Science, Computational Biology, or a related discipline.
- Peer-reviewed publications highlighting contributions to statistical or computational biology.
- Experience contributing to collaborative, multi-investigator research initiatives.
Work Environment
This is a hybrid position requiring a minimum of three days per week on-site at the University Park campus. Fully remote arrangements are not permitted. The role operates within a culture dedicated to equity, inclusion, and intellectual collaboration, where diverse perspectives are actively valued and integrated into research efforts.
Compensation & Benefits
The salary range for this position is $61,800.00 to $89,600.00. Full-time employees receive comprehensive health coverage, retirement planning support, generous paid time off, and access to a substantial tuition discount for themselves and eligible dependents. The benefits package is designed to support long-term well-being and professional development.
