Staff Data Scientist, Clinical Real World Evidence

Senior/Staff Data Scientist, Real World Evidence (Clinical)

Join a team of data scientists building a robust computational platform for advancing the R&D of new medicines. Opportunity to work across traditional industry boundaries in a fast-paced startup environment, with a diverse array of data spanning biology, computational chemistry, imaging, electronic medical records, text notes, clinical trials, and data from our labs.

Day to Day:

• Work as part of (and lead) teams of data scientists and engineers developing and deploying robust, generalizable solutions to core scientific problems
• Be comfortable with scientific risk - many of the challenges we’re trying to address don’t have known solutions.
• Use your technical knowledge and intuition to articulate and break down large problems into solvable pieces in a limited amount of time.
• Collaborate across clinical and pre-clinical teams to help make sure the models developed by you and your team are appropriate.

• MS in biological sciences, medically related field, or computer related field
• Strong understanding of multiple healthcare claims and electronic healthcare records database
• Practical experience with real world patient data - cleaning, filtering, harmonizing, etc.
• Experience conducting, analyzing and reporting observational database studies using large observational health related database resources
• Experience with multiple programming languages, such as R, Python, SQL

• Experience with statistical analysis and ML pertaining to observational studies, including potential outcome models, counterfactual regression, covariate adjustment, instrumental variables, traditional epidemiological tools, etc.

• Experience with popular analytical tools such as Pandas, Scikit-learn, Tensorflow, PyTorch, Jupyter, or spark.ml
• Experience with modern machine learning techniques pertaining to patient representation learning is a plus

• Familiarity with or exposure to traditional drug discovery and development processes and approaches is a plus
• A user-oriented, product mindset and familiarity with agile development practices a plus