Data Analyst Job at University of Chicago in Chicago

Data Analyst at University of Chicago

University of Chicago provides the following pay range:

This range is provided by University of Chicago. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$24.04/yr - $31.25/yr

About the Department

The newly established Chen Lab (https://siwei-lab.org/) is based in the Department of Human Genetics at the University of Chicago. Our research strives to catalyze repeated traversal of the 'genomic medicine cycle,' driving the discovery, biological understanding, and clinical translation of the genetic underpinnings of human disease. Our lab plays a leading role in multiple international consortia, including Epi25, the International League Against Epilepsy (ILAE), and the Genome Aggregation Database (gnomAD). Leveraging advances in genomics technologies, we have made seminal discoveries that elucidate the genetic basis underlying conditions ranging from severe neurodevelopmental disease to population-level phenotypic variation. Our work has been published in high-profile journals including Nature, Nature Genetics, Nature Neuroscience, and others. We are currently expanding efforts to build large-scale data commons for human complex disorders and to integrate emerging technologies such as AI to drive the next wave of genomic and biomedical discovery.

Job Summary

We are seeking a highly motivated and detail-oriented Data Analyst to join our team in advancing large-scale genomic studies. There are multiple non-exclusive projects you may contribute to:

• Genetic association analysis to discover genes and mutations driving disease risk.
• Multi-omics analysis to reveal biological processes underlying disease phenotypes.
• Statistical and AI/ML method development to enhance and expand the approaches above.
• Software and web platform development to support the dissemination of findings.

All of these projects are supported by well-funded international consortia (Epi25, ILAE, and gnomAD) where we lead flagship projects that have generated highly impactful and collaborative science over the years. The overarching goal is to better understand the genetic basis of human diseases and translate discoveries into novel therapeutic strategies.

Responsibilities

• Discusses, plans, and carries out research in a stimulating and collaborative environment.
• Processes and analyzes large-scale genomics datasets for disease association studies.
• Develops and/or applies statistical and AI/ML models for biologically informed gene discovery and variant interpretation.
• Builds and implements computational workflows for data quality control, annotation, and downstream analyses.
• Summarizes findings in reports, manuscripts, and presentations for internal and external dissemination.
• Maintains well-documented, reproducible code and workflows.
• Assists in analyzing data for the purpose of extracting applicable information. Performs research projects that provide analysis for a number of programs and initiatives.
• 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.
• Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs maintenance on large and complex research and administrative datasets. Responds to requests and engages other IT resources as needed.
• Performs other related work as needed.

Education & Minimum Qualifications

Minimum requirements include a college or university degree in a related field.

Work Experience

Minimum requirements include knowledge and skills developed through less than 2 years of work experience in a related job discipline.

Preferred Qualifications

• Bachelor’s degree or higher in computational biology, bioinformatics, statistics, computer science, AI/ML, or a related quantitative field.

Technical Skills or Knowledge

• Basic knowledge of genetics principles.
• Proficiency in programming languages and working with high-performance or cloud computing environments.
• Practical experience in either large-scale genomics data analysis or statistical/AI/ML method application to biological data.
• Familiarity with omics datasets and modern statistical/AI/ML methodologies in biology.

Preferred Competencies

• Strong organizational skills, attention to detail, and ability to work independently and in a team setting.
• Proactive mindset with strong communication skills to work effectively in an interdisciplinary team.
• Enthusiasm for initiating innovative secondary analyses, such as integration with multimodal functional and clinical data from external resources.

Application Documents

• Resume/CV (required)
• Cover Letter (required)

Pay Rate Type

Hourly

Pay Range

$24.04 - $31.25

Benefits Eligible

Yes

Benefits Description

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.

Accommodations

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.