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Genetic Gwas Polygenic Risk Scores Jobs (NOW HIRING)

23andMe, Inc.

Deep understanding of integrating genetics in a clinical setting, including polygenic risk scores.* Research experience using machine-learning and statistical modeling techniques to analyze large ...

AMN Healthcare

Chief of Genetics

Hagerstown, MD · On-site

$350K - $400K/yr

Whole genome or exome sequencing and polygenic risk scoring across cardiovascular, oncologic ... Medical Genetics, Genetics, Hereditary Disorders AMN Healthcare is a digitally enabled workforce ...

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$99K

$191.8K

$384K

How much do genetic gwas polygenic risk scores jobs pay per year?

As of Sep 11, 2026, the average yearly pay for genetic gwas polygenic risk scores in the United States is $191,763.00, according to ZipRecruiter salary data. Most workers in this role earn between $168,500.00 and $190,500.00 per year, depending on experience, location, and employer.

What are Genetic GWAS polygenic risk scores?

Genetic GWAS Polygenic Risk Scores (PRS) are numerical values that estimate an individual's genetic predisposition to certain traits or diseases based on the combined effects of many genetic variants identified through Genome-Wide Association Studies (GWAS). These scores are calculated by summing the effects of thousands of single nucleotide polymorphisms (SNPs), with each SNP contributing a small amount to the overall risk. PRS are increasingly used in research and clinical settings to understand genetic risk, guide personalized medicine, and inform preventive healthcare strategies. However, their predictive power can vary across populations and traits, and they should be interpreted with caution.

How do Genetic GWAS polygenic risk scores analysts typically collaborate with multidisciplinary teams in research settings?

Analysts working with Genetic GWAS Polygenic Risk Scores often collaborate closely with bioinformaticians, statisticians, clinicians, and data scientists. They play a key role in translating genomic data into actionable risk scores, requiring regular communication to align on project goals and interpret results. Effective collaboration involves discussing data quality, statistical methods, and clinical implications, ensuring the findings are robust and meaningful. This multidisciplinary teamwork fosters innovative solutions and enhances the accuracy and utility of polygenic risk assessments.

What are the key skills and qualifications needed to thrive as a Genetic GWAS polygenic risk scores analyst, and why are they important?

To thrive in this role, you need a solid background in genetics, biostatistics, and epidemiology, often supported by an advanced degree (e.g., MSc or PhD) in a relevant field. Proficiency with statistical programming languages (such as R or Python), GWAS analysis tools (like PLINK or BOLT-LMM), and experience handling large-scale genomic datasets are typically required. Strong analytical thinking, problem-solving ability, and effective communication skills are crucial for interpreting complex results and collaborating across multidisciplinary teams. These skills are essential to accurately identify genetic associations, develop reliable polygenic risk scores, and translate findings into actionable insights for research or clinical applications.

What is the difference between Genetic Gwas Polygenic Risk Scores vs Genetic Counselor?

AspectGenetic Gwas Polygenic Risk ScoresGenetic Counselor
Required CredentialsBioinformatics, statistical geneticsMaster's in genetics or counseling, certification
Work EnvironmentResearch labs, data analysis settingsClinical settings, patient consultations
Industry UsageGenomic research, risk prediction modelsPatient education, genetic testing guidance
Common Search/ComparisonGenetic risk scores, polygenic scoringGenetic counseling, genetic risk assessment

While Genetic Gwas Polygenic Risk Scores focus on analyzing genetic data to predict disease risk, Genetic Counselors work directly with patients to interpret genetic information and provide guidance. Both roles are integral to genetics but serve different functions within the industry.

What other helpful pages are available for Genetic Gwas Polygenic Risk Scores?

Other pages related to Genetic Gwas Polygenic Risk Scores:

Infographic showing various Genetic Gwas Polygenic Risk Scores job openings in the United States as of September 2026, with employment types broken down into 73% Full Time, and 27% Part Time. Highlights an 82% In-person, 9% Hybrid, and 9% Remote job distribution, with an average salary of $191,763 per year, or $92.2 per hour.

Computational Biologist

Chicago, IL • On-site

The University of Chicago
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about The University of Chicagoexternal

$60K - $80K/yr

Full-time

Medical, Retirement, PTO

Re-posted 13 days ago

University Of Chicago rating

8.1

Company rating: 8.1 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

Job description

Department
BSD MED - Genetic Medicine - Im Research Staff
About the Department
The Section of Genetic Medicine shape the future of personalized medicine with successful research programs focused on the quantitative genetic and genomic science. The Section provides extremely valuable collaborations with investigators in the Department of Medicine who are seeking to develop new and more powerful ways to identify genetic risk factors for common, complex disorders with almost immediate clinical application.
The Section of Genetic Medicine conducts impactful investigations focused on quantitative genetics, systems biology and genomics, bioinformatics and computational biology as well as through extensive collaborations of the faculty throughout the Department of Medicine, Biological Sciences Division and the University of Chicago.
Job Summary
We are seeking a lifelong learner interested in developing statistical and computational tools to sift through large amounts of data to make discoveries that can improve human health. The Computational Biologist will contribute to the development and application of statistical and computational tools across NIH-funded projects, integrating large-scale GWAS with metabolomics data to uncover mechanisms underlying complex diseases and developing polygenic risk scores that transfer genetic signals across human populations and model organisms to study addiction-related traits, COPD, type 2 diabetes, and other common diseases.
Responsibilities
  • Analyze large-scale genomic datasets including RNA-seq, whole genome sequence, and single-cell data.
  • Develop and apply statistical and computational methods to extract biological insights from high-dimensional data.
  • Develop and train deep learning models to improve upon traditional statistical methods in genomics.
  • Collaborate with disease and genomics experts to address pressing biomedical research questions.
  • Write and contribute to scientific publications and present findings at lab and consortium meetings.
  • Help train and mentor students in the lab.
  • Applies research principles and relevant subject matter knowledge relevant to administer a research project. With a moderate level of direction, manages lab and/or research-related duties and tasks. Helps develop, design and conduct research projects according to plan.
  • Takes responsibility for the following laboratory duties: recognizing abnormal results and varying conditions or procedures to correct problems; setting up and performing experiments. Analyze the meaning, significance, causes, and effects of the subject.
  • 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 2-5 years of work experience in a related job discipline.
Certifications:
---
Preferred Qualifications
Education:
  • Master's or doctoral degree in computational biology, bioinformatics, statistics, physics, or other quantitative disciplines with an interest in applying skills to biomedical research.

Experience:
  • Experience with deep learning in genomics and large language models.
  • Experience with large datasets, distributed computing, and databases.
  • Reproducible research tools and workflows (GitHub, Snakemake, Nextflow).
  • Proficiency in R and/or Python.

Preferred Competencies
  • Strong Analytical skills.
  • Problem-solving skills.
  • Organizational skills.
  • Verbal and written communication skills.
  • Ability to work independently and as part of a team
  • Willingness to explore and adopt new ideas and technologies.
  • Analytical, statistical, quantitative, and computational/programming skills.

Application Documents
  • Resume (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
Drug Test Required
No
Health Screen Required
No
Motor Vehicle Record Inquiry Required
No
Pay Rate Type
Salary
FLSA Status
Exempt
Pay Range
$60,000.00 - $80,000.00
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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