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Senior Director, Discovery Data Sciences

Senior Director, Discovery Data Sciences

GSKEdgemont, PA, US
3 hours ago
Job type
  • Full-time
Job description

Discovery Data Sciences Group Leader

Do you share a desire to advance scientific knowledge and harness the revolution in data, automation and predictive sciences to deliver measurable impacts on the success and progression of GSK's medicine discovery portfolio?

The Data, Automation, and Predictive Sciences (DAPS) function of GSK Research Technologies focuses on large-scale data generation, curation, analysis, and prediction to increase the Probability of Technical and Regulatory Success (PTRS) of assets and unlock upper quartile ambitions.

Collaboration is key, as DAPS will only be successful by working in close partnership with matrix teams within Research Technologies functions, Research Units (all therapeutic areas), the Onyx Research Data Platform and Quality Engineering and Labs (QEL) teams (R&D Digital & Tech (RDDT)), R&D AIML, and Risk & Compliance.

We are seeking a dynamic scientific leader to direct our new Discovery Data Sciences (DDS) group, a team dedicated to accelerating the discovery of new medicines for patients. This role is pivotal in delivering transformative computational and data science solutions directly to our drug discovery portfolio. You will lead a unified team that partners deeply with research units across Research Technologies (RTech) to solve their most critical scientific challenges.

A key focus will be on driving our portfolio and priority technology builds, ensuring that our most advanced predictive models and platforms are developed and deployed to maximize scientific impact.

As the leader of the new Discovery Data Sciences group, you will direct a core component of the DAPS mission. Your primary responsibility is to forge a single, cohesive team from our specialized data science groups that support biologics, genomics, discovery biology, and more. This unified group will serve as the predictive engine for R&D, enabling our vision of automated discoveryincluding Lab-in-an-Automated-Loop (LIAL) frameworksby providing the intelligence that powers the experimental cycle. Success will be achieved through deep collaboration with your peer teams across DAPS, including Automation, Cheminformatics, Protein Design & Informatics, the Research Data Office, and Discovery Engineering & Integration.

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

Key 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 pressing scientific challenges from the pipeline into actionable computational strategies and deliver solutions that accelerate decision-making and increase the probability of success.
  • Ensure that data and predictive insights are delivered accessibly and interpretably, empowering researchers to make timely, data-driven decisions within their portfolio campaigns.
  • Establish robust metrics to track the impact of predictive models and computational approaches on pipeline progression.

Strategic Vision & Organizational Architecture

  • Forge a new, unified organizational structure for the combined 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 that positions this group as the predictive engine within DAPS and the broader R&D organization.
  • Platform & Technology Leadership

  • In partnership with Discovery Engineering Sciences, guide the co-development of robust, scalable, and integrated scientific platforms, including machine learning modeling environments, automated chemical design systems, and in silico protein engineering suites.
  • Collaborate with R&D Digital & Tech (RDDT) to guarantee that all scientific applications are built for scale and can be effectively deployed, monitored, and maintained within the provided Onyx and QEL production environments.
  • Collaborate closely with Discovery Integration Sciences and Automation to design and enable the data, modeling, and software components required for our priority technology builds and future automated discovery systems (LIAL).
  • Data Asset & Governance Leadership

  • In close collaboration with the Research Data Office, drive the strategy for creating and curating high-value, proprietary data assets.
  • Ensure all data generated by the group adheres to FAIR principles and enterprise-wide data standards, making it analysis-ready and suitable for immediate use in AI / ML applications.
  • Serve as a key stakeholder and thought partner to the Research Data Office, providing expert input on data governance, quality, and lifecycle management from the perspective of a primary data generator and consumer.
  • AI / ML Innovation & Research Leadership

  • Cultivate a culture of pioneering research, fully embedding advanced AI / ML techniques (including generative AI and active learning) to solve key challenges identified through portfolio support.
  • Establish research priorities and protected time for the team to explore novel computational methods, ensuring our scientific support remains at the cutting edge.
  • Talent & Culture Development

  • Lead, inspire, and develop a global team of world-class computational scientists, data engineers, and bioinformaticians.
  • Attract and retain top-tier talent by fostering a dynamic, collaborative, and intellectually stimulating environment rooted in scientific impact and partnership.
  • Basic Qualifications

  • Ph.D. in a relevant field such as Computational Chemistry / Biology, Computer Science, Bioinformatics, or a related quantitative discipline.
  • 12+ years of experience in the pharmaceutical or biotech industry, with at least 8 years in a leadership role managing multi-disciplinary computational science teams.
  • Deep expertise in at least one, and broad understanding across several, of the following domains : cheminformatics, computational biology, protein design, structural biology, bioinformatics, and genomics.
  • A demonstrated track record of applying AI / ML to solve complex biological and chemical problems, leading to tangible project impact.
  • Preferred Qualifications & Skills

  • A Transformational Leader : Proven experience leading large-scale organizational change, unifying disparate teams, and building a cohesive, high-performance culture.
  • An Influential Collaborator : Exceptional ability to build alliances and communicate a compelling vision to stakeholders across science, technology, and executive leadership.
  • A Scientific Driver : A passion for science and a relentless focus on translating computational innovation into real-world medicines for patients.
  • An AI / ML Visionary : Deep understanding of modern machine learning, including generative models, and a clear vision for their application in R&D.
  • A Strategic Architect : Experience designing and implementing automated research frameworks is a plus.
  • A Global Leader : Proven experience managing global teams and navigating a complex, matrixed organization.
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