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Senior Data Scientist - Digital Health

Местоположение Уолтем, Массачусетс, США Кембридж, Англия, Великобритания Гейтерсберг, Мэриленд, США Идентификатор вакансии R-102340 Дата публикации 03/10/2021

At AstraZeneca, we work together to deliver innovative medicines to patients across global boundaries.  We make an impact and find solutions to challenges.  We do this with integrity, even in the most difficult situations, because we are committed to doing the right thing.

The Digital Health Oncology Data Science Team aims to transform the patient experience and clinical trial process. We will do so by deploying digital solutions to clinical trials and in the real world to decrease patient burden. The approach the team takes will incorporate clinical trial data, Real World Evidence (RWE) data, clinical free text, medical imaging, Patient Reported Outcomes (PROs), and device data to define new digital approaches to addressing the pressing problems in Oncology.

The team is looking for a Senior Data Scientist to specialize in development of innovative machine learning methods focused on multi-modal datasets including clinical trial data, RWE, imaging data, genomic data, behavioral data and other biomedical data sources to address patient burden. Applications include forecasting, time series analysis, graph modeling and analytics and reinforcement learning. This role will work closely with stakeholders and the team to develop innovative digital approaches to reduce patient burden in clinical trials and the real-world setting. The Data Scientist will also work closely with the DH Oncology Team to develop novel approaches to modeling and deriving insight from multi-modal data. Applications should have a strong foundation in statistics and experience with machine learning in a production environment.

Examples of projects the team works on include machine learning models for developing 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

  • Provides advanced data science expertise to AstraZeneca projects and recommends data science solutions.
  • Delivers advanced data science solutions to AstraZeneca projects, appropriately communicating with non-technical stakeholders.
  • Works within established frameworks to deliver a variety of tasks that support projects in meeting their objectives.
  • Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.
  • Reviews working practices and ensures non-compliant processes are escalated
  • Ensures own work is compliant within Clinical Development.
  • Collaborate in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.

Education, Qualifications, Skills and Experience


  • A minimum of a B.Sc. degree in rigorous quantitative science (such as mathematics, computer science, engineering), M.Sc. degree preferred
  • B.Sc and a minimum of 3 years of industry experience or post-doctoral work or M.Sc and a minimum of 2 years of industry experience or post-doctoral work
  • Practical software development skills in standard data science tools: Python, Agile, Code versioning (bitbucket/git), UNIX skills, familiarity working in cloud environment (AWS preferred)
  • Data visualization & interactive data visualization (interactive dashboards w/ DASH & static visualization)
  • Experience developing machine learning first products including timeseries analysis, forecasting, behavioral analysis
  • Knowledge of range of mathematical and statistical modelling techniques and drive to continue to learn and develop these skills.


  • Ph.D. degree in rigorous quantitative science (such as mathematics, computer science, engineering)
  • Experience within the pharmaceutical industry
  • Communication, business analysis, and consultancy
  • AWS experience (provisioning resources required for analytics, Kubernetes, infrastructure as code is a bonus)
  • Advanced machine learning models: transformer-based NLP models, reinforcement learning, GNNs, state-of-the-art timeseries & forecasting models
  • ML Ops experience: model tracking, model governance, multiple models in different production contexts

Why AstraZeneca?

At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognizing their potential. Join us on our journey of building a new kind of organization to reset expectations of what a bio-pharmaceutical company can be. This means we’re opening new ways to work, pioneering cutting edge methods and bringing unexpected teams together. Interested? Come and join our journey.

So, what’s next?

Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours.

Where can I find out more?

Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/

Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/

Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en

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.

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