Sr Manager, Data Scientist, Technical Developoment

About Gilead

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.

Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.

We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.

We are seeking a Senior Manager, Data Scientist, Technical Development to lead applied analytics, statistical modeling, ML/AI, and automation use cases that advance scientific insight and support priority decisions across Technical Development. This role partners with Tech Dev scientists, Digital Solutions, IT/platform teams, Quality, and other stakeholders to frame scientific questions, prototype and validate analytical approaches, and develop reusable, workflow-integrated decision-support capabilities.

Early focus areas may include predictive modeling, LLM/GenAI-enabled knowledge management and automation, image-based or process-data modeling, stability analytics, scheduling/workflow optimization, and participation in broader enterprise AI initiatives.

• Lead the identification, prioritization, and evaluation of high-value data science, AI, and analytics opportunities across Technical Development, balancing scientific impact, feasibility, scalability, and organizational priorities.
• Partner with Tech Dev scientists to prototype, test, interpret, and iterate analytical approaches in real development workflows.
• Translate scientific and operational questions into clear analytical problem statements, including intended use, assumptions, data needs, success measures, and decision impact.
• Lead cross-functional initiatives and influence scientific, digital, and technology stakeholders to align on analytical strategies, platform capabilities, data standards, and adoption approaches.
• Design and advance scientific knowledge management capabilities, including structured knowledge assets, ontologies, knowledge graphs, retrieval systems, and GenAI-enabled scientific discovery and decision-support solutions.
• Define and implement evaluation frameworks for analytical and AI-enabled solutions, including performance measurement, validation, robustness, explainability, and adoption metrics to ensure trusted scientific use.
• Build and promote reuse of analytical assets across priority Tech Dev use cases and initiatives (e.g., statistical and ML/AI models, standardized datasets and features, dashboards, automation scripts, workflow patterns, code, data definitions, and analytical methods).
• Work with Digital Solutions, IT/platform teams, and other partners to move suitable analytics from exploratory work toward scalable, supportable products and workflows.
• Contribute to enterprise LLM/GenAI and data-driven solution areas in line with Responsible AI, data governance, quality, and documentation expectations.

• BA/BS with 10+ years of relevant experience; MA/MS with 8+ years of relevant experience; or PhD with 2+ years of relevant experience in data science, statistics, computational science, engineering, informatics, or a related quantitative field.
• Multiple years of applied data science experience, including work using statistical modeling, machine learning, AI, automation, data engineering, visualization, knowledge management, or…