Caris Life Sciences is seeking a Data Scientist – Statistics & Modeling to focus on statistical modeling, clinical trial data analysis, and development of methodologies to support research and translational initiatives, aiming to generate insights that directly impact cancer research and precision medicine.
Requirements
- Strong foundation in statistical methods, including survival analysis, Cox proportional hazards modeling, and hypothesis testing.
- Experience working with clinical trial datasets and multi-source biomedical data.
- Proficiency in at least one statistical programming language (e.g., R or Python).
- Experience with SQL and working with relational databases.
- Ability to generate and interpret statistical outputs and communicate results to both technical and non-technical audiences.
- Knowledge of machine learning methods for risk prediction and treatment response modeling.
- Familiarity with regulatory standards for diagnostic or clinical trial analytics (e.g., FDA, CMS).
Responsibilities
- Design and implement statistical models to support biomarker discovery, validation, and clinical trial analysis.
- Develop methods for survival analysis, risk modeling, and treatment benefit prediction.
- Collaborate with pathologists, scientists, and clinicians to translate research questions into statistical frameworks and study designs.
- Conduct hypothesis testing and generate reproducible results for regulatory and publication purposes.
- Prepare clear, well-documented code and reports for both internal and external stakeholders.
- Support ad hoc statistical analyses and data requests in a timely and accurate manner.
- Contribute to scientific manuscripts, abstracts, and presentations.
Other
- PhD degree in Statistics, Biostatistics, Data Science, Bioinformatics, or a related field.
- 1 – 3 years’ experience in data science.
- Excellent written and verbal communication skills.
- Proficient in Microsoft Office Suite, specifically Word, Excel, Outlook, and general working knowledge of Internet for business use.
- Occasional after-hours response may be required for urgent project deadlines.
