Data Scientist – Computational Biology

Job Responsibilities

• Analyze Caris’ large-scale genomics and transcriptomics datasets to generate novel discoveries in cancer biology.
• In collaboration with machine learning experts, apply multi-modal modeling approaches integrating RNA-seq expression data with mutations, copy number alterations, fusions, protein markers, and clinical metadata.
• Translate analytical findings into improvements to the Caris clinical diagnostic platform to enhance treatment prediction and clinical insight.
• Publish results in peer-reviewed journals and present findings at scientific conferences and internal forums.
• Support collaborations with biopharma partners by providing analytical expertise, developing custom analyses, and communicating results to external stakeholders.
• Stay current with advances in oncology, cancer genomics research, and emerging analytical paradigms.

Required Qualifications

• Ph.D. in Computational Biology, Bioinformatics, or a related quantitative field; or M.S. degree with 3+ years of relevant experience.
• Demonstrated track record of novel discoveries in cancer genomics using large-scale, multi-modal datasets involving thousands of patients.
• Conceptual understanding of experimental genomics methods such as RNA-seq and exome sequencing, as well as molecular biology techniques.
• Understanding of statistical and machine learning techniques with hands-on experience applying modern models.
• Proficiency in Python and the scientific computing ecosystem.
• Strong written and verbal communication skills.
• Familiarity with Linux environments and Git.
• Proficient in Microsoft Office Suite including Word, Excel, Outlook, and internet tools.

Preferred Qualifications

• Publishing record in peer-reviewed cancer genomics journals.
• Experience analyzing cohort-level electronic health records and real-world data.
• Experience using cloud or high-performance computing environments.