Data Scientist - Innovation - PhD

Caris Life Sciences • Irving, TX • 5h ago

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 analytically strong Data Scientist to join the Innovation Team. This role will support the development and application of machine learning and statistical methods using next-generation sequencing (NGS) and related clinical and molecular data. The Data Scientist will contribute to assay development, biomarker research, and analytic pipeline execution under the technical guidance of senior and principal data scientists. The successful candidate will demonstrate sound analytical judgment, scientific curiosity, and the ability to collaborate effectively within cross-functional research teams. Opportunities may exist to contribute to publications and scientific presentations as part of Caris' ongoing innovation efforts.

Job Responsibilities

Process, curate, manipulate, and analyze large and complex NGS-derived datasets to support biomarker discovery and assay development initiatives.

Implement, test, and iterate on machine learning models and analytical workflows in alignment with established research objectives and technical direction.

Apply statistical, machine learning, deep learning, and survival analysis techniques to analyze genomic and clinical datasets and generate interpretable results.

Support the development and evaluation of explainable machine learning models for risk prediction and biomarker analysis.

Assist with the integration and analysis of multi-omics data sources (e.g., WGS/WES, transcriptomics, proteomics, metabolomics) for downstream research and clinical insights.

Execute analyses within existing analytic pipelines and contribute improvements under guidance from senior team members.

Collaborate closely with bioinformaticians, molecular biologists, geneticists, data scientists, and software engineers to support cross-functional research goals.

Prepare clear documentation, visualizations, and summaries of analytical results for internal stakeholders.

Support ad hoc analytical requests with appropriate prioritization and technical oversight.

Follow established best practices for code quality, version control, reproducibility, and data governance.

Required Qualifications

PhD in Data Science, Computational Biology, Bioinformatics, Genetics/Genomics, Mathematics, Computer Science, Engineering, or a related field, with demonstrated exposure to cancer biology or translational research.

1-5 years of relevant working experience in bioinformatics and data science.

Proficiency in programming in Python.

Familiar with Linux environment and git.

Proficient in Microsoft Office Suite, specifically Word, Excel, Outlook, and general working knowledge of Internet for business use.

Preferred Qualifications

Experience with deep learning libraries such as PyTorch or TensorFlow.

Experience with explainable ML methods (e.g., SHAP).

Knowledge of polygenic risk scores (PRS) and genetic risk prediction frameworks.

Experience working with large-scale biobanks or clinical datasets (e.g., UK Biobank, All of Us, eMERGE).

Knowledge of survival analysis and event data.

Proficiency in the suite of AWS offerings (SageMaker, HealthOmics, etc.) or Databricks.

Knowledge of wet lab sequencing processes.

Experience with interpretation of clinical health records including Electronic Health Records, insurance claims data, or patient histories.

Track record of peer-reviewed publications in relevant fields.

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.

Other

This position is based in Irving, TX (on-site).

Relocation assistance may be available for qualified candidates.

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.

Caris Life Sciences is a leading innovator in molecular science and artificial intelligence focused on fulfilling the promise of precision medicine through quality and innovation.

Caris is committed to quality and excellence at our state-of-the-art laboratories. Learn more about our tissue lab and the advanced technologies that are helping improve the lives of cancer patients.

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