Department
BSD CRI - Administration
About the Department
The University of Chicago biomedical enterprise houses three entities: The Biological Sciences Division (BSD), the University of Chicago Medicine (UCM), and the Pritzker School of Medicine. Collectively called UCM, we are one of the nation’s leading academic medical institutions and have been at the forefront of discovery, education, and clinical care since 1927. Located 20 minutes south of downtown Chicago, our Hyde Park main campus provides a single environment for learning, world-renowned basic science and clinical research, and outstanding clinical care.
The BSD is the largest academic unit within the University. The BSD is comprised of faculty from ten basic science departments, 13 clinical departments, and several Centers and Institutes. The approximately 1,300 faculty and 3,000 staff members working in the BSD collaborate across the organization to achieve our Mission, Vision, and Values (MVV):
MISSION: As part of the University of Chicago, we pursue globally impactful solutions to seemingly unsolvable challenges. Through our rigorous research, innovative education, and comprehensive care and healing, we collaborate on life-changing advancements that create meaningful results for our community and the world, including a greater, more equitable future for all.
VISION: Together, we elevate the human experience with knowledge and health care.

• Analyze clinical and other related data to identify and interpret trends in support of data requests, business cases, and proposed projects.
• Translate requirements for the design, construction, testing, and maintenance of data warehouse and related functionality.
• Design, develop, and test business intelligence outputs (including visualization) to ensure useful and insightful information using software including R, Python, Tableau, and/or Excel to support research and quality improvement initiatives.
• Test and validate data with the purpose of understanding and making conclusions to support decision-making processes.
• Assist in analyzing data for the purpose of extracting applicable information.
• Performs research projects that provide analysis for a number of programs and initiatives.
• Helps prepare results for publication, grants, and online visualizations and presentations.
• May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis.
• Collects, organizes, and may analyze information from the University’s various internal data systems as well as from external sources.
• Builds and rigorously evaluates statistical models using best practices of machine learning and statistical inference.
• Performs maintenance on large and complex research and administrative datasets.
• Contributes to the design, implementation, and validation of an efficient and reproducible data processing pipeline
• Manage a variety of information systems and data files, including large and complex files: analyzing file structure, using and creating file layouts, transforming raw data into finished products.
• Assisting with the development of analytic pipelines for natural language processing of clinical text, including providing general programming support.
• Monitor for timely and accurate completion of select datasets.
• Participate in strategic initiatives to enhance data management and reporting to support research and quality improvement initiatives.
• Collaborate closely with a cross-functional team of Data Analysts, Project Managers, Developers, and Leadership to ensure high-quality projects are performed.
• Proactively identify issues and opportunities to improve data systems and related policies as an aspect of data governance.
• Prepares project memos, summaries, presentations, reports, and other work products for dissemination targeting academic researchers and other stakeholders, as needed.
• Attend meetings and read current literature on the computational aspects of clinical research informatics.
• Respond to requests and engages other IT resources as needed.
• Analyzes moderately complex data sets for the purpose of extracting and purposefully using applicable information.
• Provides professional support to staff or faculty members in defining the project and applying principals of data science in manipulation, statistical applications, programming, analysis and modeling.
• Cleans, transforms, merges, and matches between large and complex research and administrative datasets. Plans own resources to collect, organize, and analyze information from the University’s various internal data systems as well as from external sources.
• Builds and analyzes statistical models and reproducible data processing pipelines using knowledge of best practices in machine learning and statistical inference. Serves as a single point of contact for all requests and engages other IT resources to assist as needed. May partner with other campus teams to assist faculty with data science related needs.
• Performs other related work as needed