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Genomic Data Analyst Jobs in Indiana (NOW HIRING)

Genetics Tutor

Bloomington, IN ยท Remote

$18 - $40/hr

Guides students through constructing pedigree analyses, solving linkage mapping problems, calculating allele frequencies, and interpreting genomic data. Emphasizes probabilistic reasoning and ...

Genetics Tutor

Valparaiso, IN ยท Remote

$18 - $40/hr

Guides students through constructing pedigree analyses, solving linkage mapping problems, calculating allele frequencies, and interpreting genomic data. Emphasizes probabilistic reasoning and ...

Genetics Tutor

West Lafayette, IN ยท Remote

$18 - $40/hr

Guides students through constructing pedigree analyses, solving linkage mapping problems, calculating allele frequencies, and interpreting genomic data. Emphasizes probabilistic reasoning and ...

Genetics Tutor

Fort Wayne, IN ยท Remote

$18 - $40/hr

Guides students through constructing pedigree analyses, solving linkage mapping problems, calculating allele frequencies, and interpreting genomic data. Emphasizes probabilistic reasoning and ...

Genome Analyst

Indianapolis, IN ยท On-site

$78K - $88K/yr

... genomic mechanisms, translational research in disease models, and clinical trials in rare and ... Conducts comprehensive analysis of genetic variants using Next Generation Sequencing (NGS) data in ...

... genomics, discovery pharmacology, forensics, advanced material sciences and in the support of ... Document laboratory work in notebooks/electronic notebooks and log books, perform data integrity ...

... genomics, discovery pharmacology, forensics, advanced material sciences and in the support of ... Document laboratory work in notebooks/electronic notebooks and log books, perform data integrity ...

... genomics, discovery pharmacology, forensics, advanced material sciences and in the support of ... Document laboratory work in notebooks/electronic notebooks and log books, perform data integrity ...

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Showing results 1-20

Genomic Data Analyst information

See Indiana salary details

$32.4K

$78.6K

$129.4K

How much do genomic data analyst jobs pay per year?

As of Jul 25, 2026, the average yearly pay for genomic data analyst in Indiana is $78,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $92,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Genomic Data Analyst position, and why are they important?

To thrive as a Genomic Data Analyst, you need strong skills in bioinformatics, statistical analysis, and a background in genetics or a related field, usually supported by a degree in biology, data science, or computational science. Familiarity with tools like R, Python, UNIX/Linux systems, and genomic databases, as well as experience with next-generation sequencing (NGS) data analysis pipelines, are highly valuable. Excellent problem-solving abilities, attention to detail, and effective communication skills help analysts interpret data accurately and explain findings to interdisciplinary teams. These skills are crucial for translating complex genomic datasets into actionable insights that inform research and clinical decisions.

Is 40 too late for data science?

For a genomic data analyst, age is not a barrier to entering data science, as skills in programming, statistics, and domain knowledge are more important. Many professionals successfully transition into data science later in their careers by gaining relevant certifications and experience. Continuous learning and adapting to new tools like Python, R, and machine learning techniques are key regardless of age.

What are the typical daily responsibilities of a Genomic Data Analyst?

As a Genomic Data Analyst, your typical day involves processing and analyzing large-scale genomic datasets using specialized software and scripting languages to identify genetic variations or patterns. You might collaborate with laboratory scientists, clinicians, and other data professionals to design studies, interpret results, and ensure data accuracy. Tasks often include creating data visualizations, generating detailed reports, and troubleshooting technical issues in bioinformatics pipelines. This role requires a balance of independent data analysis work and teamwork to drive research or clinical projects forward.

What does a genomic analyst do?

A genomic analyst studies genetic data to identify variations and patterns that can inform research or clinical decisions. They analyze DNA sequences using bioinformatics tools, interpret results, and often work with large datasets in laboratory or computational environments. Strong skills in genetics, programming, and data analysis are essential for this role.

What is a Genomic Data Analyst job?

A Genomic Data Analyst interprets and analyzes large-scale genomic data to derive meaningful biological insights. They work with datasets from DNA sequencing, gene expression studies, and other genomic technologies to identify patterns, mutations, or associations related to health and disease. Using bioinformatics tools, programming languages like Python or R, and statistical techniques, they help researchers, healthcare professionals, and biopharmaceutical companies make data-driven decisions. Their role is essential in fields such as precision medicine, drug discovery, and genetic research.

How to become a genomic data analyst?

To become a genomic data analyst, typically a bachelor's degree in biology, genetics, bioinformatics, or a related field is required, often supplemented by a master's degree or higher for advanced roles. Skills in programming languages such as Python or R, experience with genomic databases, and familiarity with bioinformatics tools are essential. Gaining practical experience through internships or research projects can also improve job prospects.

What is the salary of genomic data analyst?

The average salary for a genomic data analyst in the United States ranges from $70,000 to $100,000 per year, depending on experience, education, and location. Entry-level positions typically start around $60,000, while experienced analysts with advanced skills in bioinformatics and data analysis tools can earn over $110,000 annually.
What are popular job titles related to Genomic Data Analyst jobs in Indiana? For Genomic Data Analyst jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Genomic Data Analyst jobs in Indiana look for? The top searched job categories for Genomic Data Analyst jobs in Indiana are:
Infographic showing various Genomic Data Analyst job openings in Indiana as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 83% Full Time, 10% Part Time, 1% Temporary, and 4% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $78,637 per year, or $37.8 per hour.
Postdoctoral Fellow in Medical and Molecular Genetics

Postdoctoral Fellow in Medical and Molecular Genetics

Indiana University

Bloomington, IN โ€ข On-site

$45K - $61K/yr

Full-time

Posted 10 days ago


Job description

Posting Details
Position Details
Title
Postdoctoral Fellow in Medical and Molecular Genetics
Specific Title
Appointment Type
Postdoctoral Fellow
Department
IUSM - Medical & Molecular Genetics
Campus
IU School of Medicine Indianapolis
Position Summary
Postdoctoral Fellow in Statistical Genetics
The Department of Medical and Molecular Genetics at the Indiana University School of Medicine invites applications for a Postdoctoral Fellow to join the Human Evolutionary and Statistical Genetics (HESG) Lab.
The HESG Lab develops statistical and computational methods to understand human population history and the genetic basis of complex diseases. Our research sits at the intersection of population genetics, statistical genetics, and evolutionary disease genetics, with a particular emphasis on leveraging human genetic diversity to improve genetic discovery, fine-mapping, and biological interpretation.
The laboratory is currently supported by an NIH Pathway to Independence Award (K99/R00) from the National Institute of Mental Health (NIMH) and offers an outstanding environment for developing innovative quantitative methods, establishing independent research directions, and collaborating with investigators across Indiana University School of Medicine, the Broad Institute, and Massachusetts General Hospital.
Research in the HESG Lab spans three major areas. First, we develop population-genetic methods to reconstruct human population history and understand how migration, admixture, demographic change, and natural selection shape genetic diversity. Second, we develop statistical genetics methods for GWAS, fine-mapping, post-GWAS analysis, and disease-gene discovery. Third, we study evolutionary disease genetics by connecting human evolutionary history, genetic variation, and disease biology. Together, these efforts aim to transform human genetic diversity into a powerful resource for understanding complex disease mechanisms and advancing precision medicine.
Responsibilities
The successful candidate will have the opportunity to:
  • Develop novel statistical and computational methods for human genetics and complex disease research.
  • Conduct research in statistical genetics, population genetics, evolutionary disease genetics, and large-scale genomic data analysis.
  • Analyze genomic datasets from population biobanks, sequencing studies, psychiatric genetics studies, and other large-scale human genetics resources.
  • Lead independent research projects while working closely with the PI and multidisciplinary collaborators.
  • Publish research findings in leading peer-reviewed journals and present work at national and international scientific meetings.
  • Contribute to the generation of preliminary data, analytical frameworks, and methodological results that support NIH and foundation grant applications.

Training and Career Development
The HESG Lab is committed to providing a supportive and intellectually stimulating training environment. Postdoctoral fellows will receive close mentorship in developing independent research directions, writing manuscripts, presenting scientific findings, preparing grant and fellowship applications, mentoring junior trainees, and building a long-term career plan.
The position is well-suited for candidates interested in pursuing independent academic careers, research scientist positions, or leadership roles in human genetics, statistical genetics, computational biology, data science, or industry research.
What We Offer
IU School of Medicine is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.
The successful candidate will join a newly established and rapidly growing research program with strong institutional and NIH support. The laboratory emphasizes methodological innovation, rigorous quantitative thinking, reproducible research, open science, and collaborative team science. Postdoctoral fellows will have opportunities to shape the scientific direction and culture of the lab while developing independent research programs that address fundamental questions in human genetics, population history, psychiatric genetics, and complex disease biology.
Dr. Yuan's prior work provides the foundation for the HESG Lab's current research directions. His statistical genetics work includes the development of SuSiEx, a cross-ancestry fine-mapping framework published in Nature Genetics, as well as contributions to large-scale complex disease genetics studies, including a Crohn's disease exome sequencing study published in Nature Genetics. His population and evolutionary genetics work includes ArchaicSeeker2, published in Nature Communications, for detecting archaic introgression and reconstructing complex introgression histories. Building on this background, the lab continues to develop methods for reconstructing complex population histories, including MultiWaver, MultiWaverX, HierMultiMix, and the recently published HiMWA framework. Together, these studies reflect the lab's long-term goal of developing rigorous statistical methods that connect human evolutionary history, genetic diversity, and complex disease biology.
Basic Qualifications
Required Qualifications
Applicants must have:
  • A Ph.D. in Statistics, Biostatistics, Genetics, Bioinformatics, Computer Science, Mathematics, Data Science, or a related quantitative discipline.
  • Strong quantitative, computational, and programming skills.
  • Excellent written and verbal communication skills.
  • Demonstrated ability to work both independently and collaboratively.
  • Strong interest in developing statistical or computational methods for human genetics.

Preferred Qualifications
Experience in one or more of the following areas is preferred:
  • Statistical genetics
  • Human genetics
  • Population genetics
  • Evolutionary genetics
  • Bayesian statistics
  • Machine learning
  • Large-scale genomic data analysis
  • High-performance computing

Experience in human population genetics, evolutionary genetics, or related quantitative analyses is considered a plus but is not required.
Department Contact for Questions
Application
Applicants should submit:
  • Curriculum Vitae
  • Brief statement of research interests and career goals
  • Contact information for three references

though the Indiana University academic careers portal via this link
https://indiana.peopleadmin.com/postings/33803Applications will be reviewed on a rolling basis until the position is filled.
Kai Yuan, PhD
Assistant Professor
Department of Medical and Molecular Genetics
Center for Computational Biology and Bioinformatics
Indiana University School of Medicine
Principal Investigator
Human Evolutionary and Statistical Genetics (HESG) Lab
Computational Methods for Population History and Complex Disease
Email: yuankai@iu.edu
Additional Qualifications
Special Instructions
Priority Application Review Deadline
Expected Start Date
Posting Number
IUSM-02470-2026