Real World Data Scientist – MsC /RWD / Oncology / Flatiron / observational study design
For our customer a big pharmaceutical company in Basel we are looking for a highly qualified Real World Data Scientist
As a REAL WORLD DATA SCIENTIST/Epidemiologist within our Personalized HealthCare function, you will work with meaningful data to generate impactful evidence and insights on our molecules/medicines and patients, that support R&D, advance scientific and medical knowledge, and enable personalized patient care and access. This position will primarily focus on leading and executing the Real World Data Strategy and Projects to support programs across therapeutic areas (e.g. oncology and neuroscience).
You will collaborate with peers within the function and across the organization (e.g. Clinical Science, Medical Affairs, Market Access, Drug Safety, company affiliates) to design and execute studies, and implement analyses to address molecule and disease area questions. Data sources will be mainly patient level medical data that arise from observational settings, for example, electronic medical records (EMR), registries and claims data. The evidence and insights will be used to inform the research and development of our molecules, and support healthcare decisions by patients, physicians, health authorities, payers, and policy-makers.
We are looking for significant scientific and technical data science expertise in designing and conducting end-to-end prospective and retrospective observational studies, which includes defining clear study objectives, undertaking background research, protocol writing, collaborating with stakeholders from other scientific disciplines (e.g. analytics, clinical science, global access), preparing presentations as well as interpreting and communicating findings (internally and externally). Your technical and methodological expert knowledge encompasses solid understanding of the different sources of bias in RWD, different statistical tools to address them including a good understanding on causal inference techniques for observational data. Understanding of the healthcare or pharmaceutical industry environments is a key asset.
Tasks & Responsibilities
* Identify & recommend data solutions: Ask the right technical questions, understand the design needs for research and development, regulatory, medical and market access, and ideate and make recommendations on fit-for-purpose data and analytics solutions.
Expert in observational study design including the different sources of bias have a good understanding on causality / causal inference
Nice to haves:
Reference No.: 920046SGR
Role: Real World Data Scientist