Director, Science

As a science-driven healthcare analytics company with a rapidly growing customer base, Datavant is looking for an expert R programmer with experience analyzing real world data. 

As an Associate Director / Director in the Research+Analytics team, you would be part of a small team of analytic programmers executing analyses for client projects and may contribute to the development of software product features. 

This position will report to the Senior Director of Biostatistics, Programming Team Lead.

• →Autonomously conduct programming tasks, including data management for complex longitudinal analyses and use of R, SQL, and Apache Spark
• →Aid in the interpretation of programmed results (e.g., relevant sections of reports or manuscripts)
• →Aid in the design and conduct of robust real-world research, including protocol and statistical analysis plan development and ensuring appropriateness of study design, sample size and statistical methodologies proposed
• →Mentor early-career programmers 
• →May be asked to provide input on the appropriate application and prioritization of analytic product features and support their testing in collaboration with the Product Management and Engineering teams, based on use cases and input from clients and internal scientists 

• Advanced degree in biostatistics, statistics, epidemiology, or related quantitative field 
• PhD with at least 2 years of relevant experience or Masters with at least 5 years of relevant experience
• Experience processing raw real-world data files (especially from secondary sources) to obtain analysis-ready datasets, such as engaging with data from multiple tables, stringing data to create drug durations, applying complex algorithms (for example, creating pregnancy episodes), etc.
• Strong programming experience in R and SQL
• Experience working with Databricks and Apache Spark for large-scale data processing
• Proficiency in Github use
• Excellent oral and written communication skills
• Ability to self-motivate
• Collaborative, flexible, and solution-oriented

• Experience in the conduct of descriptive, prediction, and causal inference observational/epidemiological studies using secondary sources of real-world data, such as administrative claims, electronic health records, and disease registries.  Experience in the clinical trials space may meet this requirement 
• Experience with AI coding tools