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 creative, driven, and goal-oriented principal data scientist to join our innovation team. This position will be responsible for developing machine learning algorithms using NGS, contributing towards liquid biopsy assay development, as well as designing and implementing analytic pipelines to support Caris' research initiatives. The successful candidate will possess strong analytical and critical thinking skills, a solid scientific background, and excellent communication abilities. They should also have a passion for personalized medicine and be committed to staying up to date with the latest developments in cell free DNA, machine learning, and deep learning technology. Additionally, there will be opportunities to publish research results and contribute to Caris' ongoing innovation efforts.

Job Responsibilities

• Processing, manipulating, and analyzing large diverse data sets generated from NGS to develop biomarkers for cancer diagnosis, prognosis, and treatment.
• Developing, implementing, refining, and testing algorithms and workflows that achieve strategic goals in biomarker prediction, molecular profiling, and R&D objectives.
• Utilizing state of the art statistical, machine learning, deep learning, and survival analysis methods to analyze and interpret data and drive insights.
• Collaborating with cross-functional teams, including bioinformaticians, molecular biologists, geneticists, and software engineers.
• Developing state-of-the-art predictive models with both structured and unstructured data sets.
• Responding to, and managing ad hoc requests to deliver accurate, in-depth analysis/results/data, in a timely matter.

Required Qualifications

• PhD in Data Science, Computational Biology, Bioinformatics, Mathematics, Computer Science, Engineering, or a related field, with demonstrated exposure to cancer biology.
• At least 5 years of relevant experience in bioinformatics and data science.
• Proficiency in programming in Python.
• Familiar with Linux environment and git.

Preferred Qualifications

• Experience with deep learning libraries such a PyTorch or Tensorflow.
• Knowledge of survival analysis and event data.
• Proficiency in the suite of AWS offerings (Sagemaker, HealthOmics, etc.)
• Knowledge of wet lab sequencing processes.
• Experience with interpretation of clinical health records including Electronic Health Records, insurance claims data, or patient histories.

Physical Demands

• Working at a computer for the majority of the day.

Training

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

Conditions of Employment: Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check ( applicable for certain positions) and reference verification.

This job description reflects management’s assignment of essential functions. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time.

Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.