Principal or Director - Real World Evidence (RWE)

  • AstraZeneca
  • Cambridge CB2 8PA, UK
  • 22/07/2020
Full time Data Science Data Analytics Big Data Statistics

Job Description

Principal and Director level roles – Real World Evidence (RWE)

Locations: preferably Cambridge (UK)

Career levels: E or F

At AstraZeneca every one of our employees makes a difference to patient lives every day. We are building on our strong pipeline and turning ideas into life-changing medicines that benefit patients around the globe.

We are looking for MSc/PhD level quantitative epidemiologists, bioinformaticians, health informaticians, biomedical data scientists, clinicians/pharmacologists, bio-statisticians or related disciplines with a strong desire to learn and expand their skillset into the analysis of Real World Evidence (RWE).

The role holder will be a subject matter expert on the use of Real World Data and its capabilities in the use of RWD. The role holder will transform real-world clinical data into actionable insights for clinical development using statistical methods and innovative data visualizations to support decisions. The individual will also be responsible to the ideation of new methods and applications of RWE for new clinical development challenges and will be responsible for supporting new regulatory interactions using RWD.

The AstraZeneca Oncology R&D RWE group provide expert analysis and interpretation of the complex biomedical data captured in electronic health records, claims data, registries, wearables and epidemiological observations. This important work, which provides a rich window on the complicated realities of patients and diseases, is used to support the drug development process in a variety of ways, including:

  • Analysing longitudinal health data to characterise patient journeys and outcomes
  • Sifting claims and prescription data for use patterns and to support label expansion
  • Building predictive models of patient outcomes
  • Identifying patient subtypes (e.g. via biomarkers) for possible therapy development
  • Building synthetic control arms to support the interpretation of clinical studies
  • Development of algorithms for better diagnosis and identification of patients
  • Searching for evidence of adverse effects in medical histories
  • Estimating the number of eligible patients for clinical trials from databases and literature
  • Using federated networks of electronic health records for patient identification and recruitment
  • Using real world evidence to support pragmatic and hybrid trial designs
  • Partnering with external organisations to generate bespoke real world datasets

Experience in any of the following areas would be essential:

  • Health analytics and data mining of routinely collected healthcare data
  • Use of statistical and scripting languages such as R, Python and SQL
  • Clinical trials and recruitment, especially the application of synthetic control arms
  • The application of genomics in clinical care or translational medicine
  • Health economics or epidemiology, and quantitative science such as health outcome modelling

Experience in any of the following areas would be desirable:

  • Data science, machine learning and construction of predictive models
  • Clinical data standards, medical terminologies and healthcare ontologies
  • Work in a patient care or similar setting, that would allow the candidate to bring medical perspective into real-world evidence generation
  • Experience design and implementing pragmatic clinical trials

Next Steps – Apply today!

To be considered for this exciting opportunity, please complete the full application on our website at your earliest convenience – it is the only way that our Recruiter and Hiring Manager can know that you feel well qualified for this opportunity. If you know someone who would be a phenomenal fit, please share this posting with them.

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