Sumitovant is the parent company of five biopharmaceutical companies: Myovant, Urovant, Enzyvant, Altavant and Spirovant. Our companies have a robust pipeline of innovative drug treatments targeting a broad range of diseases. With a technology-enabled approach to drug discovery, development and commercialization, we remove friction from the process of bringing promising new compounds to market.

One focus of the Computational Research team is the analysis of Real-World Data (RWD), such as insurance claims and financial transaction records in order to support medical and clinical strategy, commercial evaluation, market access, business development among many topics. To achieve this goal, the RWD team maintains and constantly expands a large database containing the datasets of interest, performs analyses for various groups across the subsidiary companies and develop novel statistical methodologies fit-for-purpose. The team collaborates closely with stakeholders for analysis design, data recommendation and communication of the results in order to impact the development of new drugs.

At Sumitovant You Will:

  • Partner with stakeholders in order to understand the data and evidence needs as well as providing insight regarding the design of RWD analyses
  • Execute RWD analyses in order to support drug projects
  • Develop and apply new statistical methodologies using the billions of records available in the database
  • Help maintain our current data infrastructure and extend it with new datasets

Who You Are:

  • Degree / expertise in quantitative field with background and interest in life sciences
    • Master’s degree plus minimum 1-2 years experience or PhD required
  • Proficient in Python or R, as well as in SQL
  • Experience working with large databases is a plus
  • Experience working in the pharmaceutical industry and with RWD or related disciplines to generate scientifically rigorous evidence is preferred
  • Strong written and verbal communication skills
  • Good knowledge of statistics, including epidemiological and observational methodologies

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