Associate Director, Integrated Scientific Data Analysis & Visualization
Do you share a desire to advance scientific knowledge and capitalise on 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 deliver higher PTRS (Probability of Technical and Regulatory Success) assets and unlock upper‑quartile ambitions. Within DAPS, the Discovery Integration Sciences team is driving efforts across research to build the world’s most efficient and effective biopharma discovery platform by building and deploying innovative Lab‑in‑an‑Automated‑Loop (LIAL) systems that integrate computational intelligence with physical laboratory experimentation in adaptive learning cycles.
Responsibilities
* Design and deliver scientific visualisations and underlying data structures to surface multi‑modal scientific data generated across biopharma discovery activities in an integrated and actionable manner based on a causal mechanistic representation of disease.
* Build, test and optimise robust and performant scientific visualisations and applications that enable real time exploration of large‑scale interconnected data packages managed on GSK’s Onyx Research Data Platform and the capture of human insight.
* Collaborate across departments, with scientists evaluating integrated data packages to progress the portfolio, and with data, knowledge and software engineers, to enable robust knowledge foundations and maturation of best‑in‑class visualisations into production applications.
* Contribute to a culture of innovation, quality, and continuous learning and improvement within the team, including mentoring or upskilling other team members and continuously evaluating bioinformatics science and technology developments for potential application at GSK.
* Understand the internal and external landscape of data integration, visualisation and access principles to build, identify and create high‑value scientific visualisations.
Basic Qualifications & Skills
* Bachelor’s degree (or equivalent) in Computer Science, Data Science, Software Engineering, Life Sciences or related field.
* Extensive experience in scientific data analysis and visualisation, with a strong preference for experience in pharma/biotech.
* Extensive experience in front‑end technologies: JavaScript, TypeScript, ReactJS, AngularJS or similar.
* Extensive experience with at least one common web back‑end language: e.g. Python, Scala, Java, JavaScript (Node.js) including toolchains for documentation testing and operations/observability.
* Extensive experience with modern software development tools and ways of working (e.g. git/GitHub, DevOps tools, metrics/monitoring, …).
* Extensive experience building complex scientific data visualisations using visualisation frameworks like D3.js, Plotly, Matplotlib, or similar.
* Extensive experience building and visualising complex scientific data assets with semantically designed schemas leveraging relational and graph technologies.
Preferred Qualifications & Skills
* Specific experience with Knowledge Graph efforts.
* Experience with open‑source ontology tools, data formats and languages (e.g. Protégé, SPARQL, OWL, SKOS, SHACL, RML).
* Demonstrated experience establishing and managing external partnerships in an industrial setting.
* Track record of change leadership driving lasting adoption of scientific analysis and visualisation tools within an organisation.
Closing Date for Applications – 12th December 2025 (EOD)
We offer a competitive salary, an annual bonus based on company performance, healthcare and wellbeing programmes, a pension plan membership, and a shares and savings programme. Our Performance with Choice programme offers a hybrid working model, empowering you to find the optimal balance between remote and in‑office work.
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, colour, 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.
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