Data Scientist / ML Engineer Intern

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Work Shift

Day

Work Day(s)

Friday, Monday, Thursday, Tuesday, Wednesday

Shift Start Time

8:00 AM

Shift End Time

5:00 PM

Worker Sub-Type

Temporary

Children’s is one of the nation’s leading children’s hospitals. No matter the role, every member of our team is an essential part of our mission to make kids better today and healthier tomorrow. We’re committed to putting you first, and that commitment is at the heart of our company culture: People first. Children always. Find your next career opportunity and make a difference doing what you love at Children’s.

Job Description

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.

Goals:
-Produce a cohesive proof of concept that meet system and department goals
- Gain exposure to the tools, concepts, and practices of advanced analytics in the context of a large healthcare provider

Tasks:
-Extract, transform, process and analyze complex data sets using appropriate tools
- Follow technical guidelines and best practices for project management, source control, documentation and responsible machine learning
- Effectively collaborate with team members and stakeholders across the health system
- Communicate results and provide recommendations for improving data and/or operational workflows
- Follow department and team norms for agile work management (daily standups, sprint planning etc.)
- Contribute to organizational knowledge by participating in internal knowledge shares/seminars

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.

Experience

• Research area: research experience necessary either through previous internship, work experience, or course work; practical knowledge about the conduct of research principals required

Preferred Qualifications

• Progression toward an undergraduate or graduate degree (preferred) in Biostatistics, Health Informatics, Public/Behavioral health, Epidemiology, Statistics, Data Science, Analytics, Machine Learning, Information Systems, Bioinformatics, Computer Science, Industrial Engineering) 
• Experience with advanced analytics tools (ex R, Python)  and/or SQL data extraction and manipulation (ex: Oracle, Microsoft SQL Server) in a research, academic or business context 
• Knowledge of at least one of the following: Machine learning algorithms (ex: unsupervised clustering, logistic regression, XGBoost, lightgbm, random forest, neural networks); Classical statistics methods (ex: bivariate analysis, regression analysis, ANOVA, survival models, principal component analysis, forecasting); and/or RShiny, Plotly or equivalent data visualization and dashboarding tools (ex: Qlik, Tableau, Power BI) 
• Familiarity with at least some of the following: Use of integrated development environment (e.g., RStudio Workbench, Pycharm, Visual Studio) and notebook tools (Rmarkdown, Jupyter) to create and share reproducible analyses; Version control and issue tracking tools (ex: Azure DevOps, Gitlab, Gi