The success of Roivant’s business model depends on accurate, up-to-date knowledge of the entire space of drugs in clinical development. Building such knowledge requires 1) a scalable infrastructure for data selection, acquisition, and management, 2) predictive analytics that enable analytics on the data, 3) visualization techniques to ensure that insight translates into action.
We are a small but growing team responsible for building this infrastructure. We are looking for a talented data scientist who can engage across the range of these activities to join the team and help translate the universe of pharmaceutical knowledge into actionable insights.
Help to define and build the unstructured data strategy for drug valuation
Help to develop and build the architecture for Roivant’s Natural Language Processing document analysis pipeline
Assess and implement methodologies to build various components of drug financial models, including areas such as epidemiology, efficacy, clinical trial design, IP, etc., with an emphasis on sustainable algorithmic solutions
Build analytical tools for drug valuation on top of Roivant’s structured and unstructured data
Translate data into actionable insights for Roivant’s drug acquisition/development activities
PhD or Bachelor’s degree plus 5 years of experience
Experience in biological research
A statistical and computational background
Experience with Python, machine learning, natural language processing, data visualization preferred
Location in New York is strongly preferred, but exceptional candidates working remotely from Switzerland will be considered
Self-starting motivation and entrepreneurial spirit