Location: Cambridge (UK), Gothenburg (Sweden), Gaithersburg (USA)
Salary and Benefits: Competitive
The AI and Analytics team within AstraZeneca’s R&D Data Science and AI (DS&AI) group uses sophisticated algorithms and techniques to solve some of the hardest problems in the discovery and development of new medicines. The team uses a blend of scientific, problem solving, and quantitative skills to develop and deliver ground breaking methods addressing critical problems in our R&D environment. Our team of data scientists work right next to our other scientists and operational teams, allowing them to be close to the questions that matter and work on a broad range of the most promising opportunities quickly.
The Data Science & AI team collaborates across R&D to drive innovation through data science and AI. Together we seek to:
- Improve our understanding of disease and uncovering new targets
- Transform R&D processes
- Speed the design and delivery of new medicines for patients
Do you want to join us and apply machine learning to tackle difficult problems in drug development? As a Data Science Director, you can play a pivotal role in a rapidly growing team analysing and manipulating various types of biomedical datasets and generating the insights from our complex data that brings innovative medicines to patients faster.
In this role you will join a rapidly growing team analysing and manipulating various types of biomedical datasets and generating the insights from our complex data that brings innovative medicines to patients faster. You will apply your expertise in machine learning, quantitative data analysis and artificial intelligence to develop innovative data science solutions in clinical drug development. To achieve this, you will apply and develop new technologies/methods and work in a highly multidisciplinary environment with world leading clinicians, data scientists, biological specialists, statisticians and IT professionals.
We work on a flexible and varied portfolio of challenges that could include, but are not limited to:
- Researching and developing machine learning models on multi-modal data to improve processes and provide crucial insights to decision-makers,
- Researching and developing forecasting and optimization methods to guide decision-making about and resourcing of our drug projects
- Understanding the patient journey to optimize patient treatment pathways
- Working with drug project teams to design better drug trials, optimize their supply chains and improve trial participants’ experiences.
These challenges will require you to:
- Lead, advise on, investigate the feasibility of, and deliver data science solutions and ideas that drive value to AstraZeneca
- Apply a range of data science methodologies, developing novel data science solutions where off-the-shelf methodologies do not fit
- Translate unstructured, complex business problems into the appropriate data problem, model and analytical solutions
- Develop, implement and maintain tools and algorithms in a manner which meets regulatory and evidential requirements
- Clearly and objectively communicate results, as well as their associated uncertainties and limitations
- Constructively collaborate with a diverse set of users (global functions and local marketing companies) and partners enabling effective consensus, conflict resolution and alignment to project goals
- Mentor, coach, and support junior data scientists across multiple projects to drive the development of data science as an AstraZeneca capability
- Review and develop working practices to ensure that data science work is delivered to robust quality standards
- MSc or PhD statistics, mathematics, informatics, computer science, the physical sciences or a related subject
- Experience leading and delivering machine learning and statistical algorithms, insights and tools
- Experience Mentoring junior scientists
- Computing skills: scientific computing and scripting (R, Python, Hadoop, AWS), software development, database design and coding
- Specialist understanding of algorithm design, optimization, and deployment
- Experience manipulating and analysing large high dimensionality unstructured datasets, drawing conclusions, defining recommended actions, and reporting results across partners
- Excellent written and verbal communication, business analysis, and consultancy skills
- Customer focus - dedicated to meeting the expectations and requirements of internal and external customers
- Integrity and trust - unwavering commitment to "doing the right thing"
- A passion to apply machine learning and other data science techniques to tackle difficult problems in drug development
- PhD degree in rigorous quantitative science (such as mathematics, computer science, engineering)
- Experience in novel methods development and application
- Understanding of life sciences, with a preference for clinical drug development and the pharmaceutical environment
- Experience of end-to-end software tool/solution development and lifecycle management ideally including the RFI/RFP process, and experience with SCRUM/agile is desirable
- Multiple published papers and/or patents, contribution to open source projects