Data Scientist - Statistics & Modeling

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 detail-oriented and analytically driven Data Scientist – Statistics & Modeling to join our Computational Pathology team. This role will focus on statistical modeling, clinical trial data analysis, and development of methodologies to support our research and translational initiatives. The ideal candidate will have strong statistical expertise, experience with survival analysis and biomarker development, and the ability to translate complex analyses into actionable scientific insights.This position provides the opportunity to work with multi-modal datasets, including histopathology, molecular, and clinical data, to generate insights that directly impact cancer research and precision medicine.

Job 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.
• Ensure analytical approaches follow best practices and regulatory guidelines.

Required Qualifications

• PhD degree in Statistics, Biostatistics, Data Science, Bioinformatics, or a related field.
• 1 – 3 years’ experience in data science.
• 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.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Background in oncology, cancer biology, or translational research.
• Experience with biomarker discovery and validation studies.
• Familiarity with regulatory standards for diagnostic or clinical trial analytics (e.g., FDA, CMS).
• Prior publications in peer-reviewed scientific journals.
• Knowledge of machine learning methods for risk prediction and treatment response modeling.

Physical Demands

• Primarily computer-based work, with collaboration through in-person meetings or remote conferencing.

Training

• All job-specific, safety, and compliance training will be provided based on assigned responsibilities.

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