Works closely with other Data Scientists, Application Engineering, Product Management, and Operational teams in designing, experimenting with, and implementing machine learning to drive operational value.

Works closely with Application Engineering teams to gather and process data, as well as in surfacing various analytically based features in core products

Works on new applications of machine learning and analytic technology within Healthcare, producing quantitative, justifiable results to guide feature planning

Translates real-world Healthcare problems to mathematical frameworks Works with Product Management, Marketing, and Sales as needed to promote sales and to incorporate market and customer feedback

Data exploration, hypothesis creation (from business and product goals), testing algorithms, scaling to large data-sets and validating results will be common tasks for this role

Understands, organizes, and communicates succinctly. Familiarity with various statistical and machine learning techniques including: classification, regression, dimension reduction, clustering, and various multivariate methods

Complete familiarity with empirical approaches to estimate performance of machine learning models including: hold-out sets, cross-validation, leave-one-out testing

Demonstrated competency in R/Python predictive modeling

Demonstrated competency in RDBMS (e.g. SQL Server)