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Senior Data Scientist - Machine Learning

US - Gaithersburg - MD, US - Waltham - MA / Full Time

February 28

The Machine Learning and AI team in AstraZeneca’s Oncology Data Science & Analytics 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 Senior Data Scientist you will play a key role on the front line in this rapidly growing team working to extract insight from complex biomedical data. You will develop your leadership skills and apply and develop your expertise in rigorous quantitative data science to provide solutions to a variety of data science problems, researching, recommending and delivering novel methodologies to solve the problems that matter to the oncology pipeline.

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 analyze wearable data, linking of medical imaging data with ‘omics and longitudinal outcomes to identify and/or validate new drug targets, and much more!

Typical Accountabilities

Providing advanced data science and machine learning expertise to AstraZeneca projects, researching and recommending data science solutions, and appropriately communicating with non-technical stakeholders.

Collaborating in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.

Publishing your work to ensure that AstraZeneca drives the data science agenda in the pharmaceutical industry.

Education, Qualifications, Skills and Experience


MSc degree in rigorous quantitative discipline (such as mathematics, computer science, engineering)

Practical software development skills in standard data science tools (such as R or python)

Knowledge of range of mathematical and statistical modelling techniques, and drive to continue to learn and develop these skills

Experience in one or more of deep learning and computer vision, natural language processing, Gaussian process modelling.


PhD degree in a rigorous quantitative discipline (as above)

Demonstrated experience working with business customers to help formulate business problems as a rigorous quantitative question, and translating analysis results to business recommendations.

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