• Design, develop and deploy advanced statistical or machine learning models for credit risk, pricing, collections, fraud, and other high-impact business use cases that drive better data-driven decisions • Lead end-to-end delivery of data science initiatives from problem framing and model design through deployment, monitoring and ongoing maintenance • Partner with cross-functional teams including Portfolio Strategy, Engineering, Product, Underwriting, Sales and Collections to integrate models into our applications, and proactively identify and solve problems in critical business areas • Define and set standards for model development, code quality, and documentation; guide technical design decisions across the team • Act as a technical mentor to team members, fostering a culture of continuous learning and rigorous analytical standards • Communicate complex technical concepts and business implications to both technical and non-technical stakeholders • Build and maintain production machine learning pipelines and monitoring systems to ensure models are reliable, scalable and continuously improving

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 The Data Scientist, Data & Science Solutions at Caris Life Sciences will contribute to the delivery of analytics and research that demonstrate the value of Caris molecular and clinical data products. This role focuses on supporting analytics projects that generate biological insights relevant to drug discovery and translational research. This role will work closely with senior data scientists and cross-functional partners to analyze clinico-genomic data, develop analytical solutions, collaborate on research initiatives, and support a variety of strategic partnerships. A successful candidate will have the analytical, code-oriented mindset to write clean, reproducible code, and the communication skills and expertise needed to translate technical, scientific results for biopharmaceutical partners. Job Responsibilities - Contribute to analytics and research that support internal stakeholders and external partners. - Assist in the development and evaluation of molecular signatures and analytical approaches that leverage Caris' data to support partner research and drug discovery strategies. - Support preparation of analytical results and figures for internal reviews and client-facing discussions. - Develop and maintain tools, workflows, and automated solutions to scale data analytics and data science operations. - Support the Biopharma Solutions team with feasibility assessments and tooling to optimize workflows. - Write well-structured, well-documented, and reproducible code, including efficient queries and organized codebases. Required Qualifications - PhD in Computational Biology, Bioinformatics, Mathematics, Data Science, Engineering, or related scientific field. - Strong programming skills in Python or R, with experience developing reproducible analysis workflows. - Experience with Linux ecosystem, Git, and queries from SQL or related database families. - Experience with molecular genetics data and/or multimodal real-world data (RWD). - Ability to translate biological and scientific questions into analytical or statistical approaches and deliver data-driven insights. - Strong verbal and written communication skills, with the ability to explain complex technical concepts in clear language. Preferred Qualifications - Experience with interpretation of clinical health records including Electronic Health Records, insurance claims data, or patient histories. - Experience collaborating directly with external partners or clients, particularly in biopharma or healthcare. - Good code documentation practices and experience with workflow management packages. - Experience working in cloud or HPC clusters. Physical Demands - Will work at a computer most of the time, with some time spent collaborating with subject matter experts and business group leaders either in person or through remote conferencing. - Visual acuity and analytical skill to distinguish fine detail. - Must possess ability to sit and/or stand for long periods of time. Training - All job specific, safety, and compliance training are assigned based on the job functions associated with this employee. Other - This position may require periodic travel and some evenings, weekends, and/or holidays. Annual Hiring Range $132,000.00 - $152,000.00 Actual compensation offer to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level. The pay ratio between base pay and target incentive (if applicable) will be finalized at offer. 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.

• The Sr. Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. • This role assists in the development of the Home Depot advanced analytics infrastructure that informs decision making. • Sr. Data Scientists are expected to seek out business opportunities to leverage data science as a competitive advantage. • This role would need to be proficient in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP. • Serve as a lead on data science projects, collaborating with project/product managers. • Provide prioritization of tasks, balancing workload and mentoring data scientists on the project team. • Present insights and recommendations to leaders and business partners. • Support the building of skilled and talented data science teams by providing input to staffing needs and participating in the recruiting and hiring process.

• Design and execute data science experiments, including causal analysis, A/B tests, and offline evaluation. • Develop, evaluate, and iterate on predictive models for credit/risk scoring, revenue forecasting, and policy performance. • Own model performance and monitoring: define success metrics, investigate drift, and drive improvements to data quality and feature reliability. • Partner with Product Engineering to productionize models and analytics with emphasis on reliability, reproducibility, and maintainability. • Perform exploratory data analysis, feature engineering, and robust validation on real-world, messy data. • Communicate insights and recommendations clearly to technical and non-technical stakeholders through documentation and presentations. • Improve analytical standards, code review practices, and documentation to raise technical quality. • Mentor and support team members through pairing, feedback, and sharing best practices.