Job Description

HybridPosition Focus:Yale School of Public Health (YSPH) is seeking a highly skilled Data Scientist (DS). This is a unique opportunity for a skilled programmer motivated to produce rigorous, empirical evidence to improve policy. The ideal candidate is an expert programmer fluent in R or Python, has experience manipulating health care datasets and working with advanced machine learning libraries (Scikit-learn, Keras, TensorFlow). Exceptional understanding of causal inference and a commitment to YSPH’s mission are crucial. The individual will analyze data to solve research questions using cutting-edge techniques. The individual will be embedded within DSS where they will work across teams and data systems to preform novel linkages between programs, enabling new research into previously unanswerable questions. As part of this, the DS will build new infrastructure to support advanced analytics and rigorous policy evaluations which can scale to accommodate the future needs of DSS.The DS will develop and refine analytic plans with state-of-the-art statistical and econometric techniques to address research and quality improvement objectives at both Yale and DSS. They will develop novel predictive modelling capabilities within DSS using advanced machine learning techniques to improve the efficiency of current and future member-facing campaigns. After deployment, the DS will refine models with the goal of improving accuracy and targeting, and quantifying whether sophisticated techniques (e.g., deep learning) provide tangible benefits over current models.