Data Scientist

BSD CTD - Gen3 SPM
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 impactful 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 https://gdc.cancer.gov/, https://gen3.org/, https://stats.gen3.org/, and https://ctds.uchicago.edu/.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.
The Center for Translational Data Science at the University of Chicago is seeking a 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 contributes 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; organizes, harmonizes, and analyzes data sets or develops tools to assist such processes; uses various technologies to visualize data or enable data visualization; and creates applications of general value to the project and product owners.

The job uses best practices and 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. The job is responsible for managing operational protocols.

• Interpreting data from multiple sources.
• Developing software programs and services, software notebooks and software scripts for data transformation, data integration, data analysis and data visualization.
• Enhancing previously developed in-house open-source data platforms, systems, applications and notebooks.
• Performing various types of analysis involving multiple data sets.
• 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.

Minimum requirements include a college or university degree in related field. Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

• Master’s degree, in one of the following fields: math, statistics, computer science, data science, physical science, or biological science.

• Strong foundation in areas of statistics, mathematics, and computer programming.
• Additional expertise in areas of data science, machine learning and related topics.

• Strong skills in problem solving and quantitative/qualitative analysis.
• Able to organize and prioritize work assignments to meet project needs.
• Strong communication skills.
• Able to quickly comprehend requirements and assignments and then explain his/her solutions in both writing and speech.

• Office environment.

• Resume (required)
• Cover Letter (preferred)

Research
Individual Contributor
Exempt
Monthly
40
Yes
No
No
No