Data Scientist – Computational Biology

Caris Life Sciences•Boston, MA

21h•$125,000 - $150,000•Onsite

About The Position

Caris Life Sciences is seeking a talented Data Scientist – Computational Biology to leverage one of the world’s largest multi‑modal cancer datasets to develop new insights into cancer biology and improve patient outcomes. This role supports the development of novel precision medicine diagnostics and therapies by working deeply with large‑scale clinical cancer genomics data. Working closely with machine learning experts, clinicians, and other computational biologists, this position contributes to advancing Caris’ clinical diagnostic platform and impacts hundreds of thousands of patients annually who rely on Caris testing to identify effective therapies from their cancer genomes.

Requirements

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.

Nice To Haves

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.

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.