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Lead the design and implementation of AI/ML models and workflows to analyze large-scale biomedical and translational research data. Collaborate with interdisciplinary teams to develop open-source data platforms and translate scientific requirements into actionable data science strategies.
Requires a university degree in a related field and 5-7 years of professional experience in data science. Preference is given to candidates with advanced degrees in quantitative fields and experience in academic or health research environments.
About the Department
Job Summary
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.
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.
Has a deep understanding of methods to analyze complex data sets for the purpose of extracting and purposefully using applicable information. May develop and maintain infrastructure that connects data sets.
Guides staff or faculty members in defining the project and applies principals of data science in manipulation, statistical applications, programming, analysis and modeling.
Calibrates data between large and complex research and administrative datasets. Guides and may set the operational protocols for collecting and analyzing information from the University's various internal data systems as well as from external sources.
Performs other related work as needed.
Minimum Qualifications
Work Experience:
Certifications:
Advanced degree in Computer Science, Data Science, Statistics, Mathematics, Bioinformatics, or a relevant quantitative field.
Experience working in data science roles, preferably in an academic, research, or health/science environment.
Experience with collaborative open-source projects and software engineering best practices.
Experience working in multi-disciplinary academic teams.
Knowledge of biomedical and translational research data sources is a significant advantage.
Knowledge of hardware specifications required for AI/ML research and projecting resource needs and use in public clouds environments like AWS and GCP.
Knowledge of and experience with data and applications of interest to CTDS, including, but not necessarily limited to, AI data commons, AI data meshes, Gen3, NCI Genomic Data Commons, cancer genomics, biomedical imaging data, human clinical data.
Expertise in designing and implementing machine learning, deep learning, and statistical models for research and production.
Experience with biomedical data.
Experience collaborating on manuscripts and submitting papers for peer-reviewed, scientific publications.
Advanced skills in problem solving and quantitative/qualitative analysis.
Able to organize and prioritize work assignments to meet project needs and work independently to identify and address needs beyond assigned tasks.
Strong communication skills to effectively convey complex findings while serving as a reference and subject matter expert for staff, faculty members, and Gen3 users.
Ability to quickly comprehend requirements and assignments and then explain his/her solutions in both writing and speech.
Ability to learn new skills quickly and manage complex projects.
Proficiency in Python, R, and other relevant programming languages; experience with open-source data science platforms, technologies, and cloud environments.
Outstanding analytical, problem-solving, and project management abilities.
Proven track record mentoring and leading project teams and communicating technical issues to diverse audiences.
Excellent written and verbal communication skills.
Hybrid office/remote.
Resume/CV (required)
Cover Letter (preferred)
The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.
When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.
Job Family
Role Impact
Scheduled Weekly Hours
Drug Test Required
Health Screen Required
Motor Vehicle Record Inquiry Required
Pay Rate Type
FLSA Status
Pay Range
The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.
Benefits Eligible
The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.
Posting Statement
The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.
Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.
All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.
The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu. Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.
Frontier research, global impact.
The Becker Friedman Institute for Economics (BFI) serves as a hub for cutting-edge analysis and research across the entire University of Chicago economics community, uniting researchers from the Booth School of Business, the Kenneth C. Griffin Department of Economics, the Harris School of Public Policy, and the Law School in an unparalleled effort to uncover new ways of thinking about economics. We put those ideas into action by translating rigorous research into accessible and relevant formats, and proactively disseminating it to key decision-makers around the world. Read more: bfi.uchicago.edu/about/ Follow us on Twitter: twitter.com/BeckerFriedman Subscribe to our monthly newsletter: bfi.uchicago.edu/subscribe
Offices: 5757 S University Ave., Chicago, IL 60637 , US
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