Senior Director, Discovery Data Sciences

GSK
Stevenage
2 months ago
Applications closed

Related Jobs

View all jobs

Vice President, Head of Discovery Data Science

Senior Manager, Data Science - eBay Live

Western Europe Practice Head - Data Science (Machine Learning/Artificial Intelligence (ML/AI)

Director/Snr Director, Data Science Consulting - Machine Learning/Artificial Intelligence (ML/AI)

Director, Data Science - Measurement & Optimization

Senior Data Scientist

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 discovery—including Lab-in-an-Automated-Loop (LIAL) frameworks—by 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

Portfolio Impact & Scientific Partnership:

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.

(Qualifications & Experience)

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.

#GSK-LI

• If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $207,075 to $345,125.

The US salary ranges take into account a number of factors including work location within the US market, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.

If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.

Please visit to learn more about the comprehensive benefits program GSK offers US employees.

Why GSK?
Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

Important notice to Employment businesses/ Agencies

GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.