Data Science Director, Oncology
Data Science Director, Oncology
Location of Position: Either Gaithersburg Maryland OR Waltham Massachusetts
The Machine Learning and AI team in AstraZeneca’s Oncology Data Science group is where we develop and apply sophisticated algorithms and techniques to solve the hardest problems in oncology drug discovery and development. The team uses their scientific, quantitative, and problem-solving skills to work on a broad range of challenges across the whole oncology portfolio, working collaboratively with other scientists across a range of disciplines to scope, define, and deliver projects that both advance the state of the art in data science and accelerate the delivery of innovative medicines to patients.
As a Data Science Director you will play a key role in this rapidly growing team working to extract insight from complex biomedical data. You will apply your leadership skills and your wide expertise in rigorous quantitative data science to provide solutions to a variety of data science problems in high-risk and high-impact situations. You will help to set the direction for the team and you will help to educate the whole oncology therapeutic area in the possibilities, opportunities, and challenges raised by modern quantitative data science.
Examples of projects the team works on include developing machine learning models for digital biomarkers, patient risk stratification for clinical trials, new algorithms for survival analysis, approaches to quantitatively analyse wearable data, linking of medical imaging data with ‘omics and longitudinal outcomes to identify and/or validate new drug targets, and much more!
- Provides advanced data science expertise to cross-functional AstraZeneca projects and drives delivery of advanced data science solutions in high pressure and high impact situations, appropriately communicating with a range of cross-functional senior stakeholders.
- Applies a range of data science methodologies, can fluently use a range of data science techniques, is recognised as expert on one or more specific data science methodologies, and develops novel data science and machine learning solutions where off-the-shelf methodologies do not fit.
- Leads moderate (4-5 person) data science projects with cross-functional teams or impact.
- Coaches/mentors junior data scientists and educates the wider business in the opportunities produced by modern quantitative data science.
- Publishes work to ensure that AstraZeneca drives the data science agenda in the pharmaceutical industry.
- Collaborates in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.
- Develops collaborations with external academic or commercial enterprises and maintains an external profile as an expert in one or more machine learning/data science areas.
Education, Qualifications, Skills and Experience
- MSc degree in rigorous quantitative science (such as mathematics, computer science, engineering).
- Extensive hands-on experience applying and developing data science and machine learning tools in practice.
- Practical software development skills in standard data science tools (such as R or python) and database languages.
- Excellent communication, business analysis, and consultancy.
- Extensive knowledge of mathematical and statistical modelling techniques.
- Demonstrated experience articulating business questions and using mathematical techniques to arrive at an answer using available data.
- PhD degree in rigorous quantitative science (such as mathematics, computer science, engineering)
- Experience within the pharmaceutical industry
- Agile project management techniques.
- Delivery of impactful cross-functional data science projects.
- Publication history / contribution to external open source projects.
- Experience in the development and application of novel mathematical and statistical methods.
- In-depth experience of working in a global organization with complex/geographical context.
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.