Senior Director, AI Data Science

Exelixis•Alameda, CA

5d•$244,000 - $346,000•Onsite

About The Position

The Senior Director, AI Data Science is a senior leader accountable to help shape and execute the strategy, operating model, and innovation roadmap for AI/ML and data science in support of the Data and Statistical Sciences and wider Development organization. A key focus is ensuring operational efficiency gains. This role helps establish the scientific and methodological standards that translate complex clinical, operational, translational, and real-world datasets into high-quality, actionable insights that inform drug-development decisions. As part of the Center of Data Excellence, the Senior Director builds and leads a multidisciplinary team; helps shape the AI/ML investment and platform strategy; and serves as a thought leader and partner across Biostatistics, Statistical Programming, Clinical Data Management, IT, and the broader R&D organization.

Requirements

Bachelor's degree in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics or a related quantitative field and a minimum of 15 years of experience; or, Master's degree in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics or a related quantitative field and a minimum of 13 years of experience; or, PhD in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics or a related quantitative field and a minimum of 12 years of experience; or, Equivalent combination of education and experience
Significant experience leading the development and deployment of AI/ML and data science solutions in a clinical, pharmaceutical, or life-sciences setting, including in GxP-regulated environments.
Demonstrated experience leading and building teams (including managing managers), setting functional strategy, and managing budgets and external partnerships.
Proven track record influencing executive and cross-functional stakeholders and translating advanced analytics into portfolio-level decisions.
Experience establishing AI governance, validation and compliance frameworks; familiarity with CDISC standards (SDTM, ADaM) and clinical endpoint analysis strongly preferred.
Strategic leadership; ability to help set the operating model and multi-year roadmap for the AI/ML and data science function.
Advanced command of AI/ML and statistical methodology, including supervised/unsupervised learning, NLP, and Generative-AI, with the judgment to set standards for rigor and interpretability.
Working fluency in Python, R, and SQL sufficient to guide technical direction and evaluate solution quality.
Strong understanding of modern data platforms (Databricks, AWS), MLOps/LLMOps, version control (Git/GitHub), and reproducible, secure, audit-ready architectures.
Advanced understanding of the clinical development process and regulatory requirements (ICH, GxP) and AI governance in a regulated setting.
Executive-level communication, influencing, and stakeholder-management skills across technical and non-technical audiences.
Proven people leadership, mentorship, and organizational development capability.
Strong business acumen, including budget ownership and vendor/partnership management.

Nice To Haves

Familiarity with CDISC standards (SDTM, ADaM) and clinical endpoint analysis strongly preferred.

Responsibilities

Help define and drive the multi-year AI/ML and data science strategy, roadmap, and operating model for the function, aligning investments with portfolio priorities and enterprise objectives.
Lead and develop a high-performing team; set goals, allocate resources, manage performance and drive succession and talent development.
Establish standards and acceptance criteria for AI/ML model development, validation, interpretability and responsible/Generative-AI use in a regulated environment.
Serve as a senior scientific and strategic partner to Biostatistics, Statistical Programming, Clinical Data Management, IT and broader R&D, helping shape strategies that enable efficiencies and portfolio decisions.
Guide the design and scale-up of analytics products, LLM-based and Generative-AI workflows (e.g., automated TLF review, protocol digitalization), and decision-enablement dashboards from prototype through production hand-off.
Oversee the data platform, pipeline and reproducibility strategy on Databricks and cloud infrastructure, helping set standards for MLOps/LLMOps, version control, security, and audit-readiness.
Contribute to the AI governance, risk-management and compliance framework in cross-functional partnerships.
Represent Exelixis externally through publications, conference presentations, white papers, and industry engagement.
Champion a culture of scientific rigor, innovation, mentorship, and continuous learning across the data science team.
Performs other duties as assigned
Complies with all policies and standards