Director, Head of Research Data Integration & Analytics

The Director, Head of Research Data Integration & Analytics leads the strategic development and implementation of robust, FAIR (Findable, Accessible, Interoperable, Reusable) data analytical systems and advanced AIML and predictive modelling solutions across VIDRU. This role is accountable for conceiving and delivering the digital roadmap of the entire research lifecycle, transforming raw experimental outputs into standardized, analysis-ready data assets, and embedding cutting-edge AI methodologies into daily operations by refining high-impact use cases.

This role is accountable for establishing and maintaining world-class data standards, governance, and quality for datasets, accelerating infectious disease research and vaccine development. Leveraging advanced AI/ML and predictive modeling, this role ensures seamless access to high-quality data and actionable insights, working together with scientists within Discovery Technologies and across scientific areas, and embedding software engineering best practices directly into the scientific process. This role drives the promotion of digital literacy and fluency across VIDRU, ensuring alignment with Research Tech and the R&D Digital Network.

The Head leads and mentors a world-class team, ensuring scientific excellence, strategic alignment with the Head of VIDRU Data Sciences and VIDRU R&D project/platform leaders, and adherence to top scientific and industry standards for all deliverables.

What You'll Do:

• Provides strategic vision and leadership for research data integration and advanced analytics initiatives within VIDRU Data Sciences, with a focus on accelerating infectious disease research through FAIR data and AI/ML and transforming raw experimental outputs into analysis-ready data. This includes promoting the adoption of cutting-edge AI methodologies into daily operations and refining high-impact use cases.
• Leads and manages a multidisciplinary team of data scientists, data architects, and scientific software/research engineers, fostering a culture of high performance, scientific innovation, and continuous professional development.
• Directs the design, development, and implementation of robust, scalable integrated data systems and automated, product-grade data processing and integration pipelines (e.g., for cloud computing) to consolidate and harmonize diverse bio-clinical datasets, including multi-omics, preclinical, translational, and early clinical data.
• Establishes and enforces world-class data standards, quality control processes, and governance frameworks (FAIR principles) to ensure data integrity, reliability, and reusability across all VIDRU research initiatives, from lab bench to final analysis, in collaboration with Research Technologies
• Drives the development and application of advanced analytical methodologies, including deep learning, biomedical computer vision, and predictive modeling, to extract deep biological and clinical insights from integrated datasets. This includes promoting collaborative knowledge sharing and aligning with tech providers on emerging innovations.
• Collaborates closely with DPLs, VDLs, PILs, TPLs, and clinical sciences teams, as well as lab scientists within Discovery Technologies and scientific areas, to understand their data needs and deliver integrated datasets robust, scalable analytical workflows.
• Partners with experimental scientists to optimize VIDRU data flows, ensuring high-quality data generation aligned with FAIR principles from the outset of experiments.
• Drives innovation in research data integration and predictive analytics by partnering closely with GSK's AIML, Research Tech and R&D Tech organizations, leveraging product-grade software development practices to scale successful research pipelines into reusable and sustainable assets.
• Ensures that data and analytical deliverables are at the highest research and industry standards regarding scientific excellence, quality, security, and timelines, translating complex data into actionable insights with reproducibility and reliability.
• Communicates complex data landscapes, integration strategies, and analytical findings effectively to internal and external stakeholders, acting as a bridge between biologists, data scientists, and IT engineers. This role also involves mentoring scientists in leveraging LLMs and other digital tools for research and development breakthroughs.
• Contributes to the definition and implementation of VIDRU Data Science scientific strategy, processes, and objectives, ensuring alignment with the Head of VIDRU Data Sciences and the overall GSK Vaccines & Infectious Diseases R&D strategy, maintaining digital fluency with RTech and the R&D Digital Network.

Basic Qualifications:

• PhD or equivalent experience. Data Science, Computer Science, Bioinformatics, Computational Biology, Statistics, Engineering, or equivalent, with a strong focus on data systems, advanced analytics, and molecular biology insight.
• Research experience and publication record in relevant areas, demonstrating leadership in establishing integrated data environments and delivering impactful data-driven insights from datasets in an R&D setting.
• Eight to ten years of relevant scientific experience, including four years of direct/matrix people management and international leadership responsibilities (e.g. principal investigator for international R&D projects in relevant areas).
• Proven capacity to use the theoretical background and education to solve actual problems of R&D projects working and leading teams in cross-functional setting. This role shall act as a global reference person for the function and perform people management and coaching of global staff.

Preferred Qualifications:

• Demonstrated strong proficiency / publication record in one or more of the following areas:
  • Designing and implementing robust, product-grade data systems and integration pipelines (e.g., cloud computing) for diverse bio-clinical datasets in cloud systems and HPC environments.
  • Developing and enforcing FAIR data governance frameworks and data quality standards for scientific research data.
  • Advanced AI/ML techniques including deep learning, biomedical computer vision, and predictive modelling on clinical and molecular data.
  • Expertise in managing, integrating, and analyzing multi-omics data (genomics, transcriptomics, proteomics) and associated metadata, with deep understanding of data types like FASTQ, BAM, VCF
  • Molecular biology insight applied to data interpretation and model development, with familiarity with laboratory processes and experimental design.
  • Proficiency in cloud-based data platforms and technologies (e.g., GCP, Azure) for large-scale scientific data processing and analytics.
  • Experience with version control and automated testing for scientific software development.
• Good programming, data analytics and modelling skills.
• Excellent line management skills.
• Excellent business understanding of the pharmaceutical industry.
• Good knowledge of vendors and state-of-the-art solutions for molecular design.

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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.

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