Reference Number: JO-2105-468535
Senior Real World Evidence Scientist
Rate: Negotiable
Job Type: Contract
Location: Cambridge

Senior Real World Evidence Scientist
650 a day
6 month contract

Do you have expertise in, and passion for, Real World Evidence work? Then this might be the one for you!

A leading company in the healthcare industry, with a mission to enrich the lives of others. Its our business to support balanced living, not only for our patients, but also for our employees. Our benefits program is flexible enough to meet employees varying needs, offers valuable choices, and is highly competitive.

Oncology is driven by speed. Here you will be backed by leadership and empowered at every level to prioritise and make bold moves. Be a fearless decision-maker. Speak up and constructively challenge. Powered to take smart risks based on scientific evidence. Here its our scale, agility and passion that makes sure we deliver fast, every time.

The Role
We are looking for MSc/PhD level epidemiologists, bio-statisticians, biomedical data scientists, clinicians/pharmacologists or related fields with a strong desire to learn and expand their skillset into the analysis of Real World Evidence (RWE)
The ideal candidate for this role will have deep understanding of epidemiology and will bring a consistent track record of delivering value through the use of routinely collected data from healthcare settings to provide health analytics and insights in both Public Health, Pharmaceutical Research and Development and Commercial context.

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:

  • Developing real world cohorts of patients matching clinical trial inclusion exclusion criteria
  • 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 and external 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
  • 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

Essential Requirements

  • MSc/PhD in data science or other advanced degree in life sciences with post-doctoral or other training/work in Medical Informatics or related field
  • Use of statistical and scripting languages such as R, Python and SQL
  • Clinical trials and recruitment, especially the application of synthetic control arms
  • Experience in supporting pharmacoepidemiology studies with proven track record of advancing approaches with data science
  • Demonstrated ability to build long-term relationships with partners at senior levels, understand relevant scientific/business challenges at a deep level and translate into a programme of informatics activities to deliver defined value
  • Ability to lead & manage multi-disciplinary epidemiological projects
  • Strong background of delivering large, cross functional projects
  • Experience working in a global organisation and delivering global solutions

Desirable Skills

  • Health analytics and data mining of routinely collected healthcare data
  • The application of genomics in clinical care or translational medicine
  • Health economics and quantitative science such as health outcome modelling
  • 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
  • Experience in the use of Instant Health Data

Please apply or send your CV to luke.sandilands@cpl.com

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