The Data Science Intern must have ability to perform exploratory data analyses, create effective data visualizations and have exposure to the theory and application of predictive (machine learning) and/or inferential (classical statistics) methods. As part of this internship, they will work side by side with full time data scientists, ML Engineer, business intelligence and reporting analysts to complete an internship project that may have a clinical, financial or operational focus. A final project presentation will be given to department leadership. Example projects include: - Python / ML focus (primary): Support the development and operationalization of predictive models at various lifecycle stages (e.g., exploratory data analyses for proposed features or prediction targets, development of model training, evaluation, and monitoring pipelines etc.), with a focus on predictive models for capacity management that use advanced time series forecasting methods. - R / stats focus: Enhance advanced analytics dashboards and applications (e.g., SPC ChartR, BMH Recidivism ) , with a focus on hardening existing R package development for automation of statistical process control charts. The Children's Intern program allows interns the opportunity to gain hands-on experience related to their field of study by working on meaningful projects alongside Children’s professionals. Intern responsibilities may include project management, event planning and support, logistics, data base management, research, and analysis. Interns may explore career paths and apply for full-time positions upon successful completion of the program.