Data Scientist & AI Researcher

Department

BSD CTD - Data Science

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. Learn more at (Use the "Apply for this Job" box below). https://gen
3.org/, .gen
3.org/, and .

The Center for Translational Data Science at the University of Chicago 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; organize, harmonize, and analyze data sets and develop tools to assist such processes; use various technologies to visualize data or enable data visualization;

and create applications of general value to the project and product owners. The job uses best practices and advanced knowledge of data manipulation, statistical applications, programming, analysis and modeling in order to implement projects related to the University's various internal data systems as well as from external sources.

This at-will position is wholly or partially funded by contractual grant funding which is renewed under provisions set by the grantor of the contract. Employment will be contingent upon the continued receipt of these grant funds and satisfactory job performance.

• Leading the interpretation of data from multiple sources.
• Developing and implementing software programs and services, software notebooks and software scripts for data transformation, data integration, data analysis and data visualization.
• Building, validating and evaluating AI/ML models.
• Contributing to and taking a leadership role in the enhancement and maintenance of previously developed in-house open-source data platforms, systems, applications and notebooks.
• Performing various types of analysis involving multiple data sets.
• Leading data science projects and initiatives within purview, by 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.
• Leading the conceptualization, design, and execution of 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.
• Assisting in providing leadership for design of user-facing computational resources.
• Serving 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 data science projects that involve developing computational tools and services for data engineering, data manipulation, statistical analysis, and modeling.
• Collaborating closely with faculty, researchers, and stakeholders to translate scientific and user requirements into actionable data science strategies and solutions.
• Staying current with developments in data science, machine learning, artificial intelligence, and related…