VP & Head , Statistical Innovation & Data Science, Open to flexible working
Statistical innovation is revolutionising clinical development plans and clinical trial designs across industry. The increased use of synthetic patients/control arms, adaptive designs, platform trials, quantitative decision-making, prediction modelling are all approaches which are yielding significant R&D efficiencies (resource, time, money) when applied. The field is rich in terms of further novel methods to explore, pilot and industrialise across both clinical and non-clinical R&D. The emerging but very related discipline of Data Science has also been proven to result in business value. Once in place the role would bring together our two, currently separate teams (~ 20 FTE) thereby leveraging their significant combined potential, grow the size of the combined group further by bringing in additional external top talent, and extend the reach of our impact to even greater levels across R&D.
Design, implement and embed an organisational structure, strategy and three-year roadmap which capitalises on the integration of the statistical innovation and statistical data science teams, and further increases their impact to R&D.
Build strategic and successful partnerships with senior leaders across R&D (RDLT and RDLT-1) in order to identify and implement increased opportunities for statistical and data scientific transformational innovation. Initial focus areas include Regulatory, RWE, Clinical Operations, Portfolio Analytics, Finance.
Monitor key emerging innovative statistical and data science methodologies, form relationships with external innovators, and run prioritised experiments to identify ideas which will add most business value. Drive education and integration of emerging methods into internal roadmaps where there is business value in doing so.
Effectively communicate statistical information to both technical and non-technical audiences, creating a compelling case for the company's statistical & data science innovation efforts with internal constituents, as well as external parties.
Augment the company's network by bringing to GSK new and valuable academic relationships, which can be effectively leveraged by R&D and the company at large in pursuit of its business goals.
Maintain strong external presence with relevant regulatory and industry bodies to capture and action relevant intelligence; influence external thought leaders; and be a talent magnet to attract statistical methodology and data science key talent to GSK.
Member of the Biostatistics Leadership Team, with accountability for co-developing and driving forwards GSK's overall Biostatistics strategy and ensuring full alignment of SIDS team priorities with those of the broader Biostatistics group.
Competencies - Interpersonal and leadership skills
- A track record of effective leadership in a variety of roles including interfacing with partner groups to shape the business and drive business improvement / create value.
- Broad appreciation of the drug discovery / development process and a proven ability to bridge disciplines to influence and shape decision-making and culture.
- A strong sense of initiative, urgency, drive, pragmatism and judgement - an ability to make things happen.
- Will have external statistical presence and a strong network across the industry/academia.
- A champion of effective, novel methodologies.
- Proven ability to deliver to demanding deadlines.
- Effective influencer of many different personality types across all levels of seniority.
- Proven ability to develop skills and capabilities, with demonstrated leadership in the application of innovative approaches with high-level business impact.
- Comfortable operating with and being effective despite ambiguity.
- MSc or PhD (preferred) Statistics
- International reputation in basic and/or applied statistical methodology, excellent publication record in major scientific journals demonstrating expertise in both Bayesian and frequentist statistics.
- Well-honed leadership, communication & influencing skills. A track record of building, leading and managing successful teams.
- Significant experience in statistics in support of biopharma R&D from pharmaceutical/biotechnology industry and/or academia.
- Strong knowledge of the statistical, regulatory and scientific landscapes.
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