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Genomic Variant Analyst Jobs in Chicago, IL (NOW HIRING)

Leveraging advances in genomics technologies, we have made seminal discoveries that elucidate the ... and variant interpretation. * Builds and implements computational workflows for data quality ...

Leveraging advances in genomics technologies, we have made seminal discoveries that elucidate the ... and variant interpretation. * Builds and implements computational workflows for data quality ...

Leveraging advances in genomics technologies, we have made seminal discoveries that elucidate the ... and variant interpretation. * Builds and implements computational workflows for data quality ...

Leveraging advances in genomics technologies, we have made seminal discoveries that elucidate the ... and variant interpretation. * Builds and implements computational workflows for data quality ...

Genomic Variant Analyst information

See Chicago, IL salary details

$39.1K

$75.7K

$121K

How much do genomic variant analyst jobs pay per year?

As of May 28, 2026, the average yearly pay for genomic variant analyst in Chicago, IL is $75,749.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $81,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Genomic Variant Analyst, and why are they important?

To thrive as a Genomic Variant Analyst, you need a strong background in genetics, molecular biology, and bioinformatics, typically supported by a relevant degree such as in genomics or computational biology. Experience with genomic data analysis tools (like GATK, VEP, or IGV), next-generation sequencing (NGS) platforms, and familiarity with databases such as ClinVar are essential. Attention to detail, problem-solving skills, and effective communication are important soft skills for interpreting results and collaborating with multidisciplinary teams. These capabilities ensure accurate variant identification, meaningful clinical interpretations, and successful integration of genomic data into research or healthcare.

What are some common challenges faced by Genomic Variant Analysts when interpreting complex genetic data, and how are they addressed?

Genomic Variant Analysts often encounter challenges such as distinguishing between benign and pathogenic variants, managing large volumes of sequencing data, and staying updated with rapidly evolving databases and guidelines. To address these, analysts rely on established variant classification frameworks, utilize collaborative review with clinical teams, and leverage specialized bioinformatics tools. Continuous professional development and participation in case discussions help ensure accurate interpretations and effective collaboration with genetic counselors and physicians.

What does a Genomic Variant Analyst do?

A Genomic Variant Analyst is a specialist who examines genetic data to identify and interpret variations within genomes, such as mutations or structural changes in DNA. Their work is crucial for understanding genetic contributions to diseases, guiding clinical decision-making, and advancing personalized medicine. They use bioinformatics tools and databases to analyze sequencing data, annotate variants, and assess their significance. Genomic Variant Analysts often collaborate with clinicians, researchers, and laboratory staff to ensure accurate and meaningful interpretation of genomic information.

What is the difference between Genomic Variant Analyst vs Bioinformatics Technician?

AspectGenomic Variant AnalystBioinformatics Technician
Required CredentialsBachelor's or Master's in Genetics, Bioinformatics, or related field; experience with genomic data analysisAssociate's or Bachelor's in Bioinformatics, Computer Science, or related field; basic scripting skills
Work EnvironmentLaboratories, research institutions, biotech companiesResearch labs, hospitals, biotech firms, computational environments
Employer & Industry UsageGenomics research, clinical labs, pharmaceutical companiesData processing, supporting genomic research, data management

The Genomic Variant Analyst focuses on interpreting genetic variations and analyzing sequencing data, often requiring advanced bioinformatics skills. In contrast, the Bioinformatics Technician typically handles data management, basic analysis, and supporting research activities. While both roles work within genomics and bioinformatics, the analyst role involves more complex data interpretation and analysis, whereas the technician provides essential support functions.

What are popular job titles related to Genomic Variant Analyst jobs in Chicago, IL? For Genomic Variant Analyst jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Genomic Variant Analyst jobs in Chicago, IL look for? The top searched job categories for Genomic Variant Analyst jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Genomic Variant Analyst jobs? Cities near Chicago, IL with the most Genomic Variant Analyst job openings:
Infographic showing various Genomic Variant Analyst job openings in Chicago, IL as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $75,749 per year, or $36.4 per hour.
Data Analyst

Other

Medical, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


University Of Chicago rating

8.2

Company rating: 8.2 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

106th of 528 rated colleges and universities


Job description

Data Analyst Position

The newly established Chen Lab 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) exciting 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. As a member of our team, you will gain hands-on experience working with real-world data at the population level and/or in clinical setting. These datasets include genomic and phenotypic information from hundreds of thousands of individuals and represent several of the largest initiatives of their kind worldwide. You will have the opportunity to collaborate with an international, interdisciplinary network of leading researchers and clinicians and to produce results with direct clinical and public health implications.

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.
Minimum Qualifications

Education:

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


Work Experience:

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


Certifications:

---

Preferred Qualifications

Education:

  • 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 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)


When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.

Job Family

Research

Role Impact

Individual Contributor

Scheduled Weekly Hours

40

Pay Rate Type

Hourly

FLSA Status

Non-Exempt

Pay Range

$24.04 - $31.25

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

Yes

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.


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