Manager of Data Science

· PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Epidemiology, or related field (or equivalent practical experience)

· 7+ years of experience building machine learning or statistical models deployed in production environments

· 2+ years of management experience

· Experience working on healthcare claims and EHR data across a variety of therapeutic areas

· Strong SQL, Python, and best practices for developing code for software products

· Strong statistical and machine learning fundamentals

· Demonstrated ability to translate business priorities into data science products in cross-functional collaboration

· Excellent oral and written communication

· Experience translating research into production to build novel deep learning models

BranchLab is a healthcare AI company focused on predicting health outcomes to improving how regulated organizations make decisions.

Our mission is to enable better healthcare decisions by applying AI in a way that is privacy-safe, rigorous, and designed for real-world use.

We are seeking a Data Science Manager to lead a team of data scientists and drive the development and deployment of innovative disease modeling approaches using rigorous statistical, epidemiological, and machine learning techniques. These models will be used for privacy-first pharmaceutical commercialization. The ideal candidate will have experience developing and deploying models into production, experience in a player-coach role turning innovative research projects into products, and the ability to evangelize data science and create vision and motivation. You will work closely with cross-functional leaders to define and execute on our product strategy.

· Work with cross functional leadership to understand business needs and prioritize the most impactful projects to develop products that drive business impact

· Lead large-scale data science projects from planning to execution and delivery of productionized ML/AI models

· Build and retain a team of high performing data scientists

· Communicate about results and deliverables to internal and external stakeholders

· Research industry trends and standards to proactively drive areas of improvement