Data Scientist – Computational Biology

At Caris, we understand that cancer is an ugly word—a word no one wants to hear, but one that connects us all. That’s why we’re not just transforming cancer care—we’re changing lives.

We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day: “What would I do if this patient were my mom?” That question drives everything we do.

But our mission doesn’t stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare—driven by innovation, compassion, and purpose.

Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.

Position Summary
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.

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.

Physical Demands

• Primarily office‑based role requiring prolonged periods of sitting and computer use.

Training

• All job‑specific, safety, and compliance training are assigned based on the job functions associated with this position.

Other

• This position may require periodic travel and occasional evening or weekend work.

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Annual Hiring Range

$125,000 - $150,000

Actual compensation offer to candidate may