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Principal Data Scientist - R&D Oncology

Plats New York, New York, USA Jobb-id R-075556 Datum inlagd 02/25/2020

Job Description / Capsule

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 Principal 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 apply and develop your leadership skills and 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 machine learning models for developing 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!

Typical Accountabilities

  • Provides advanced quantitative expertise to AstraZeneca projects and researches and recommends appropriate data science solutions, appropriately communicating with a range of stakeholders.
  • Develops novel data science solutions where off-the-shelf methodologies do not fit.
  • Leads small (2-3 person) data science projects of defined scope.
  • Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.
  • Coaches/mentors junior data scientists and others to drive the development of data science as an AZ capability.
  • Works within established frameworks to deliver a variety of tasks that support projects in meeting their objectives.
  • 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

Essential

  • MSc degree in rigorous quantitative science (such as mathematics, computer science, engineering)
  • Extensive hands-on experience applying data science tools in practice.
  • Practical software development skills in standard data science tools (such as R or python)
  • Extensive knowledge of mathematical modelling and statistical modelling techniques, and drive to continue to learn and develop these skills.
  • Communication, business analysis, and consultancy.
  • Minimum 5+ years of work experience

Desirable

  • PhD degree in rigorous quantitative science (such as mathematics, computer science, engineering).
  • Experience within the pharmaceutical industry.
  • 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.

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