Director, Real World Data Platform and Portfolio Lead
About the role
Business Introduction
Summary
Core Accountabilities
- Lead and execute above disease area/tumour type RWD partnerships, build partnerships built around expanding RWD capabilities and identifying new opportunities to access population level health datasets. Where relevant partner with Translational Sciences on RWD partnerships linked to -omics, biobanks and other translational cohorts.
- Ensure partnerships offer scale to drive GSK's RWE ambition and ensure operational execution of evidence generation relating to data access and analysis
- Partner in key regions and with regional leaders where population level health data can be leveraged for research, positioning GSK as a leading partner in large observational research and quantitative innovation and enabling
- Act as strategic lead for the internal RWD domain for GSK's data offices, ensuring engineering, programming and AI teams have clear input on wider data strategy plans.
- Partner with Real World Data Engineering team to guide pipeline strategy and data product roadmap
- Represent RWD and Development Sciences in the cross-functional data governance forum, ensuring centralised expectations of good data governance are translated into RWD specific domain plans.
- Inform data linkage strategy across our RWD portfolio and in prospective observational studies
- Partner with DevOps to ensure use of RWD portfolio for clinical operations planning and execution
- Deliver and maintain the baseline inventory of RWD assets that underpins portfolio assessment and decision making
- Facilitate partnerships which enhance usability and impact of RWD for R&D, Medical and Commercial teams, act as strategic link between functions and share and combine needs when appropriate
- Work with therapy area aligned data strategy leads and other internal data owners around common deliverables to inform upcoming governance decisions and support business case and financial modelling for new investments ahead of upcoming governance.
- Inform technology and infrastructure strategy to prioritise re-usable infrastructure and enable efficient use of third-party vendors and partner hosted trusted research environments
- Ensure platform and tools strategy compliantly uses RWD and keep internal networks abreast of access opportunities, including but not limited to agentic interfaces.
- Prioritise and monitor resource management across active RWD initiatives based on enterprise value and wider data and analytics strategy
- Set and monitor clear KPI's around partnerships and data value, bring key delivery metrics to organisational execution
- Influence data governance and AI readiness efforts to ensure high quality, analysis ready and FAIR data.
Basic Requirements
- Advanced degree (MSc or PhD) in life sciences or quantitative field (Epidemiology, Biostatistics, HEOR, data science preferred)
- Demonstrated track record of data strategy ownership and execution in application to drug development including experiences in wide and complex cross-functional organisations
- Leadership skills in influencing and mobilising stakeholders to a common goal
- Experience and knowledge of RWD sources and partners, spanning multiple geographies, understanding of country and regional health data landscapes, critically assess opportunities for research
- Exceptional portfolio project management and organisational skills, particularly within a complex dynamic organisation.
- Ability to communicate with clarity, vision and purpose
- Understanding of current regulatory and payer guidance of use or Real World Evidence/Data in decision making.
- Knowledge of key data strategy concepts in relation to RWD; FHIR, tokenisation and linkage, synthetic control arms, Common Data Models (CDMs) and context specific LLMs
Preferred Requirements
- Strong knowledge and experience of observational research methodology, including study designs and impact of data quality on research validity.
- 'Hands on' programming, coding skills and demonstrated experience with RWD
- Experience with data engineering and architecture, including working in or deploying trusted research environments
- Experience in AI/ML enablement and deployment of AI workflows
- Demonstrated experience of strategic partnerships with human patient level data including biomarkers, -omics and other biological measures and samples linked to clinical or real-world outcome data
Closing date for applications is Thursday 29th October
Skills
Artificial Intelligence (AI), Business Analysis, Data Analysis, Data Mining, Digital Fluency, Digital Transformation, Organization Transformation, Process Improvements, Process Innovation, Product Development, Product Management, Project Management, Regulatory Compliance Management, Security System Design, Strategic Planning
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