Associate Director, Translational Data Sciences

GSK•Upper Providence, PA

23h•€82,500 - €137,500•Hybrid

About The Position

This role contributes to translational data science work to turn genetics and multi-omics data into clear, actionable insights. The Associate Director will partner closely with translational scientists, programme teams, AI/ML and platform colleagues. The role values curiosity, scientific rigour, clear communication and a practical engineering mindset. This position offers visible impact on early discovery and clinical translation, with strong opportunities to grow scientific and leadership skills. The role is based in the United Kingdom and offered on a hybrid working model.

Requirements

Physical sciences (Maths, Computer Science, Physics, Chemistry, Engineering etc) or Biological sciences (Biology, Biochemistry, Bioengineering etc) undergraduate degree or Medical degree.
PhD in data science, computer science, computational biology, bioinformatics, or a closely related discipline.
Hands-on experience analysing large-scale genetic and multi-omics datasets and integrating these with clinical or phenotypic data.
Strong programming skills in Python, and experience delivering reproducible, production-quality analysis (version control, testing, documentation).
Experience building or owning end-to-end analytic pipelines and workflows in a research or R&D setting.
Clear written and verbal communication skills with experience presenting technical results to non-specialist stakeholders.
Ability to work effectively in multidisciplinary teams and to manage competing priorities.

Nice To Haves

Experience in translational settings within pharma, biotech or clinical research, with track record of influencing project decisions.
Familiarity with machine learning or advanced statistical methods applied to molecular or clinical data.
Experience working with single-cell, spatial, proteomic or other emerging omics modalities.
Experience with cloud platforms, trusted research environments or scalable compute systems.
Track record of peer-reviewed publications, presentations or external collaborations.
Experience leading small teams, mentoring staff, or coordinating cross-functional projects.

Responsibilities

Lead design, delivery and interpretation of translational analyses using genetics, genomics, proteomics, and clinical phenotypes to inform target, biomarker and patient-selection decisions.
Own end-to-end analytical workstreams: data ingestion, quality control, analysis, reproducible pipelines and clear reporting to programme teams.
Translate scientific questions into robust computational approaches and present results to diverse stakeholders in written reports and concise briefings.
Partner with AI/ML, platform and bioinformatics teams to operationalise methods and scale reproducible analysis in secure computing environments.
Mentor and coach scientists and analysts; contribute to team skill-building and collaborative problem solving.
Represent the team in cross-functional programme meetings and in external collaborations when needed.
Deliver reproducible, well-tested analytic pipelines for large-scale genetic and multi-omic datasets.
Produce high-quality translational interpretations that directly inform project decisions.
Build strong working relationships across biology, clinical, AI/ML and platform teams.
Ensure analyses meet data governance, privacy and traceability standards in the UK and relevant jurisdictions.
Evaluate and adopt new methods and tools when they add clear translational value.
Support knowledge sharing through presentations, documentation and peer review.