Senior Director, Discovery Data Sciences

Role Summary

Senior Director, Discovery Data Sciences (DDS) at GSK, leading a unified data science group to accelerate medicine discovery through advanced computational and data science solutions. Partners with Research Technologies and R&D units to solve key scientific challenges, drive portfolio impact, and deliver automated discovery capabilities.

Responsibilities

• Act as the primary data science partner to research line leaders within RTech, embedding your team to directly support portfolio projects across all therapeutic modalities.
• Translate scientific challenges from the pipeline into actionable computational strategies and deliver solutions that accelerate decision-making and increase the probability of success.
• Ensure data and predictive insights are accessible and interpretable, enabling researchers to make timely, data-driven decisions.
• Establish robust metrics to track the impact of predictive models and computational approaches on pipeline progression.
• Forge a unified organizational structure for the data science groups, creating a cohesive model based on core scientific and technical functions (e.g., Predictive Modeling, Generative Design, Data Platform Engineering, Bioinformatics).
• Develop and execute a long-term strategic roadmap positioning the group as the predictive engine within DAPS and the broader R&D organization.
• Guide co-development of robust, scalable platforms (ML modeling environments, automated design systems, in silico protein engineering suites) in partnership with Discovery Engineering Sciences.
• Collaborate with R&D Digital & Tech (RDDT) to ensure applications are scalable and deployable within Onyx and QEL environments.
• Partner with Discovery Integration Sciences and Automation to design data, modeling, and software components for priority technology builds and automated discovery systems (LIAL).
• Drive strategy for creating high-value, proprietary data assets in collaboration with the Research Data Office; ensure data adheres to FAIR principles and is ready for AI/ML applications.
• Provide input on data governance, quality, and lifecycle management from the perspective of a primary data generator and consumer.
• Cultivate a culture of pioneering AI/ML research, embedding techniques such as generative AI and active learning to solve key challenges.
• Establish research priorities and protected time for exploring novel computational methods to keep scientific support at the cutting edge.
• Lead and develop a global team of computational scientists, data engineers, and bioinformaticians; attract and retain top talent through a collaborative environment focused on scientific impact.

Qualifications

• Ph.D. in Computational Chemistry/Biology, Computer Science, Bioinformatics, or related quantitative field.
• 12+ years of pharma/biotech experience, with at least 8 years in a leadership role managing multi-disciplinary computational science teams.
• Deep expertise in cheminformatics, computational biology, protein design, structural biology, bioinformatics, and genomics; strong track record applying AI/ML to solve complex problems with tangible impact.
• Transformational leadership with experience unifying large teams and building a high-performance culture.
• Ability to build alliances and communicate a compelling vision across science, technology, and executive leadership.
• Passion for translating computational innovation into real-world medicines for patients; strong understanding of modern ML, including generative models; experience with automated research frameworks is a plus.
• Global leadership experience managing teams in a matrixed organization.

Skills

• Advanced data science and AI/ML expertise; experience with predictive modeling, generative design, and data platform engineering.
• Strong collaboration and stakeholder-management skills across scientific and technical domains.
• Strategic roadmap development and organizational design capabilities.
• Proficiency in managing data governance, data assets, and FAIR data principles.
• Experience with automated discovery systems and lab automation concepts (LIAL) is advantageous.

Education

• Ph.D. in a relevant field (see Qualifications).

Additional Requirements

• Willingness to be based 2-3 days per week at a GSK R&D site in the USA (Upper Providence, PA; or Cambridge Tech Square, MA) or the UK (Stevenage).