Head of Data Science & Analytics - Digital Health R&D Oncology
Job Description : Head of Data Science and Analytics - Digital Health R&D Oncology
Digital health, the point at which healthcare, technology, data and analytics converge, is the subject of great promise, with the World Health Organisation believing it has the potential to improve health for everyone. At AstraZeneca, we’ve been working hard to make this a reality, with the years of experience we have accumulated enabling us to now embed digital health at scale across R&D. To achieve our goal of improving patient experience and outcomes AstraZeneca has Digital Health as one of top 4 strategic priorities for the company, details on digital health strategy can be found here .Oncology is the largest therapeutic area within AstraZeneca and second highest cause of death globally, with AstraZeneca’s ambition to eliminate cancer as a cause of death.
The Head of Data Science and Analytics for Digital Health R&D will be a key leader to drive our digital health strategy through data and analytics, helping to design and lead the data and analytic planning and implementation across Digital Health R&D Oncology programs. This includes but is not limited to: digital therapeutic analysis plans, real world evidence analysis, psychometric analysis, and ML/AI to support more efficient identification of treatment benefits vs harms (e.g. signal detection of treatment emergent adverse events, disease progression, construction of novel endpoints to characterize safety and tolerability) and Disease Management algorithms for Oncology. Responsible for building and leading a novel data science team with a global footprint through a combination of internal FTE and strategic external partnerships. Adopting a DevOps approach working with engineers and developers to release analytical models that are repeatable and scalable. Recognised externally as a thought leader and expert within own area of specialization.
- Lead a talented technical team, working with the head of Oncology Digital health to develop the strategy for digital health solutions in Oncology and lead the implementation of data science and analytics solutions that can help patients get better outcomes in Oncology.
- Design and lead both the data & analytic planning, including oversight of implementation across all Digital Health R&D programs.
- This includes but is not limited to: digital therapeutics analysis plans, real world evidence analysis, psychometric analysis, and ML/AI to support more efficient identification of treatment benefits vs harms (e.g. signal detection of treatment emergent adverse events, disease progression, construction of novel endpoints to characterize safety and tolerability) as well as, disease management systems for Oncology
- Design and implement ML information extraction
- Probabilistic matching algorithms and models
- Research and develop innovative, scalable solutions
- Identify data sources and analyze large, complex datasets to extract insight
- Partner with key internal stakeholder to deliver: IT, Biometrics, partner data science functions
- Collaborate with R&D Data Hub leadership to ensure data is standardised, integrated and exposed in a way that facilitates the goals of the advanced analytics programme
- Develop and implement a standardised framework for analytics projects, from requirements capture through to benefits demonstration
- Define and implement strategies for managing analytical models and monitoring their performance over time
- Championing the development of infrastructure and analytics environments that facilitate the delivery of value from the Data Science and Analytics team.
- Drive key advanced analytics project delivery decisions, such as whether to “buy versus build”
- Provides input to the Digital Health R&D Strategy and Oncology TA Strategy from a Data Science perspective
- Leads, mentors, evaluates and develops the team within Data Science & Analytics to ensure that the area achieves its’ objectives and complies with all relevant regulations and laws
- MSc/PhD in Statistics, Mathematics, Data Science relevant field with experience in pharma/healthcare or other relevant area
- Conceptual, analytical and strategic thinking
- Creative, innovative, solution-focused
- Curious, embraces new ways of problem solving, new ideas, new ways of working
- Expertise and experience with development and applications of software as a medical device
- Managerial experience of both data scientists and engineering teams
- Strong communication skills and ability to build relationships
- Ability to serve as “translator” between scientific problems to data science solutions
- Ability to apply expertise to complex problems, problem solving and with a quality focus
- Proven leadership promoting motivation and empowering others to accomplish individual, team and organizational objectives
- Experience working with and architecting analytics solutions in AWS
- Experience defining strategies and approaches to AI/ML model monitoring, maintenance and management
- Experience delivering AI/ML models from conception, through development and into production
- Experience working with IT partners for business solutions
- Able to manage to budget and productivity targets/responsibilities.
- Expert problem solving and conflict resolution.
- Diligence – attention to detail and ability to manage a program of concurrent activities
- Resilience – ability to overcome and motivate others in the face of a changing environment
- Knowledge of the latest technical and regulatory expectations
- Significant experience with NLP problems
- Experience using AI/ML to combine data from multiple modalities in the pursuit of novel insights
- Understanding of and experience with developing and delivering “Explainable AI” solutions
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.