• Develop and implement advanced analytics on top of noisy, heterogeneous RiskOS data to understand user behavior, product usage, fraud patterns, and workflow effectiveness; translate findings into concrete product and risk strategy improvements. • Architect and build scalable data pipelines and production ML workflows, collaborating with data engineering to ensure robust, reliable, and efficient data processing for both batch and streaming use cases. • Lead the design, execution, and analysis of experimentation frameworks to optimize user journeys, feature adoption, and workflow performance across the RiskOS platform. • Lead the creation and evaluation of Generative AI solutions (LLMs, agents, prompt‑based tools) that automate analytics, power case review and investigation assistants, streamline documentation, and enhance RiskOS workflows and reporting. • Define rigorous evaluation frameworks for GenAI solutions, including offline benchmarks, human‑in‑the‑loop review, safety and hallucination checks, and impact measurement in production. • Partner with platform and engineering teams to define and build core RiskOS data science infrastructure, including feature stores, model‑serving APIs, evaluation services, and monitoring frameworks for both traditional ML and GenAI systems. • Own end‑to‑end deployment of production‑grade solutions: packaging models and GenAI workflows, integrating with RiskOS services, establishing SLAs, and instrumenting telemetry, alerting, and feedback loops. • Develop and automate tools for model evaluation, stress testing, backtesting, and adversarial scenario simulation to ensure robustness and operational resilience—especially in high‑risk fraud and compliance contexts. • Enable product and risk teams through self‑serve analytics and tools: build dashboards, template analyses, and GenAI‑driven assistants that help non‑technical users explore RiskOS data, tune workflows, and debug decisions. • Collaborate cross‑functionally with product, engineering, risk, solution consulting, and customer‑facing teams to translate business requirements into data‑driven solutions and actionable insights, particularly for fraud and risk use cases on RiskOS. • Mentor and provide technical guidance to other data scientists and analysts, modeling best practices in experimentation, software engineering hygiene, GenAI safety, and rigorous model evaluation. • Ensure all solutions adhere to best practices in data privacy, security, and compliance, especially when handling sensitive PII and financial data in regulated fintech and public‑sector environments. • Contribute to company‑wide standards for ML and GenAI explainability, risk evaluation, feature logging, and documentation, helping raise the overall AI bar across Socure. • Communicate complex technical concepts and findings clearly to both technical and non‑technical stakeholders, including executive leadership and external partners.

• Work with analysis of large volumes of data to identify insights and support data-driven decisions; • Develop, implement and optimize machine learning models and algorithms using Python; • Take data and analytics solutions to scale using Data and AI services on GCP; • Write efficient SQL queries and perform optimization for data extraction and manipulation; • Collaborate with cross-functional teams to understand business challenges and turn them into analytical solutions; • Design and implement data pipelines to support machine learning processes; • Create clear and concise visualizations and reports for stakeholders; • Stay up to date on trends and emerging technologies in Data Science and Artificial Intelligence;

• 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.