Position Summary
- Caris Life Sciences seeks a Data Scientist to expand, test, and validate a suite of molecular biomarkers to improve the standard of care for cancer patients.
- Research role within the Caris signature development program focused on statistical or machine-learning predictions of phenotypic treatment response from genotypic data on Caris molecular sequencing platforms.
Job Responsibilities
- Contribute to analytics and research supporting internal stakeholders and external partners.
- Develop and evaluate molecular signatures and analytical approaches leveraging Caris data for partner research and drug discovery strategies.
- Prepare analytical results and figures for internal reviews and client-facing discussions.
- Develop and maintain tools, workflows, and automated solutions to scale data analytics and data science operations.
- Support the Biopharma Solutions team with feasibility assessments and tooling to optimize workflows.
- Write well-structured, well-documented, reproducible code, including efficient queries and organized codebases.
Required Qualifications / Skills
- PhD in Computational Biology, Bioinformatics, Mathematics, Data Science, Engineering, or related field.
- Strong Python or R programming skills; experience creating reproducible analysis workflows.
- Linux ecosystem experience; Git; SQL (or related) database queries.
- Experience with molecular genetics data and/or multimodal real-world data (RWD).
- Ability to translate biological/scientific questions into analytical/statistical approaches and deliver data-driven insights.
- Strong verbal and written communication skills.
Preferred Qualifications / Skills
- Experience interpreting clinical health records (EHRs, claims, patient histories).
- Collaboration with external partners/clients (biopharma/healthcare).
- Code documentation practices and workflow management packages.
- Experience with cloud or HPC clusters.
Other
- Periodic travel and some evenings, weekends, and/or holidays; all job-specific and compliance training assigned based on job functions.