• Delivers analytical solutions using programming, data mining, statistics, machine-learning, and visualization techniques. • Responsibilities include querying databases, data processing, supervised and unsupervised machine learning, deploying production models, and communicating findings. • Writes clean, performant, reusable code to perform repeatable analyses & to train, and deploy models to multiple environments. • Assists in making strategic data-related decisions by analyzing and manipulating data and building models to assist in the clinical and operational setting. • Creates database-to-deployment pipelines for models using the vital programming languages (primarily R, Python, SQL). • Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices. • Performs exploratory data analysis to gauge the need for or appropriateness of sophisticated analytical methods. • Tests and validates code to ensure robustness of data applications.