Director, Integrated Scientific Data Analysis and Visualization

About the position 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 at GSK by building and deploying innovative Lab-in-an-Automated-Loop (LIAL) Systems that integrate computational intelligence with physical laboratory experimentation in adaptive learning cycles. Each LIAL System will deliver a domain leading scientific discovery solution that leverages and extends state-of-the-art scientific methods by engineering technologies to create integrated discovery systems that empower GSK research scientists with the latest tools. As Director, Integrated Data & Visualization in the Discovery Integration Sciences team, you will be responsible for leading activities to integrate GSK’s foundational causal biology data with data generated through discovery processes and make the resulting data products Findable, Accessible, Interoperable, and Reusable (FAIR) and available to R&D scientists, both directly through visualizations/interfaces and via agentic systems for real-time decision making. In this role, you will work and lead across scientific and technical disciplines with a strong focus on causal mechanistic understanding to deliver impactful solutions, build trusting relationships and realize lasting business value in a matrix environment. This position is based 2-3 days per week in Stevenage or London.

Responsibilities

• Develop and maintain a clear understanding of the evolving needs of Causal Biology Tech Build, and of the current landscape of available solutions, identifying where existing software components can be adopted, licensed and/or modified to meet specific needs.
• Design and deliver scientific visualizations 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 visualizations 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 visualizations 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, visualization and access principles to build identify and create high-value scientific visualizations.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Software Engineering, Life Sciences or related field.
• Experience in scaled scientific (including genetic and genomic) data workflows, analysis and visualization, with a strong preference for experience in pharma/biotech.
• 10+ years of experience in front end technologies: JavaScript, Typescript, ReactJS, AngularJS or similar.
• 10+ years of experience with at least one common web backend language: e.g. Python, Scala, Java, Javascript (Node.js) including toolchains for documentation testing and operations/observability.
• 10+ years of experience with modern software development tools and ways of working (e.g. git/GitHub, DevOps tools, metrics/monitoring, …).
• Experience building complex scientific data visualizations using visualization frameworks like D3.js, Plotly, Matplotlib, or similar.
• Experience building and visualizing complex scientific data assets with semantically designed schemas leveraging relational and graph technologies.

Nice-to-haves

• Specific experience with technologies for curating, storing, and querying Knowledge Graphs.
• 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 visualization tool within an organization.

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