Data Scientist & AI Researcher

About the Department

The Center for Translational Data Science (CTDS) at the University of Chicago is a research center whose mission is to develop the discipline of translational data science to impact problems in biology, medicine, healthcare, and the environment. We envision a world in which researchers have ready access to the data needed and the tools required to make data‑driven discoveries that increase our scientific knowledge and improve the quality of life.

We architect ecosystems of large‑scale commons of research data, computing resources, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery.

The Center for Translational Data Science is seeking a Staff Data Scientist to support a diverse range of research projects. Data Scientists work in a collaborative interdisciplinary team and play a critical role in AI/ML tooling, features, and improvements for our open‑source software systems and applications, analyzing data, and in understanding and representing user requirements to internal and external stakeholders in our translational data science projects and products.

Under the leadership of team or project leads, a person in this position will be a key contributor to the design and implementation of algorithms, AI/ML models, and workflows to enable the discovery of valuable information in large volumes of data from various sources. The role encompasses organizing, harmonizing, and analyzing data sets, developing tools to assist such processes, using various technologies to visualize data or enable data visualization, and creating applications of general value to the project and product owners.

• Lead the interpretation of data from multiple sources.
• Develop and implement software programs and services, software notebooks, and scripts for data transformation, integration, analysis, and visualization.
• Build, validate, and evaluate AI/ML models.
• Contribute to and take a leadership role in the enhancement and maintenance of previously developed in‑house open‑source data platforms, systems, applications, and notebooks.
• Perform various types of analysis involving multiple data sets.
• Lead data science projects and initiatives within purview, relaying data analysis and model deployment best practices, enhancing the technical knowledge of peers, and helping develop data science skills in junior employees and interns.
• Conceptualize, design, and execute sophisticated data science projects and AI/ML solutions for research and production environments.
• Establish and enforce data governance, quality assurance processes, and operational protocols for large, complex data sets from internal and external sources.
• Assist in providing leadership for design of user‑facing computational resources.
• Serve as a reference for staff, faculty members, and Gen3 users as a technical subject matter expert by applying principles of data science to define and scope projects involving computational tools and services for data engineering, manipulation, statistical analysis, and modeling.
• Collaborate closely with faculty, researchers, and stakeholders to translate scientific and user requirements into actionable data science strategies and solutions.
• Stay current with developments in data science, machine learning, artificial intelligence, and related fields, and adopt new methods and technologies to advance research goals.
• Communicate complex technical concepts and project results clearly to technical and non‑technical audiences, and present findings at internal and external forums.
• Develop and maintain infrastructure that connects data sets, calibrate data between large and complex research and administrative datasets, and set operational protocols for collecting and analyzing information from the university’s internal data systems and external sources.
• Perform other related work as needed.

• College or university degree in a related field.
• 5–7 years of work experience in a related discipline.

• Advanced degree in Computer Science, Data Science, Statistics, Mathematics,…