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Genomic Data Scientist Jobs (NOW HIRING)

The Harvard Medical School Department of Biomedical Informatics seeks a skilled Genomic Data ... Bachelor's or Master's degree in Bioinformatics, Computational Biology, Data Science, or a related ...

The Harvard Medical School Department of Biomedical Informatics seeks a skilled Genomic Data ... Bachelor's or Master's degree in Bioinformatics, Computational Biology, Data Science, or a related ...

Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq, WES/WGS, epigenetic, or ... Apply advanced statistical, machine learning, and data-mining techniques to extract meaningful ...

Our technology powers scientists around the world, translating AI capabilities into tools that ... genomic data systems that power next-generation biological models and accelerate human health ...

The Lead Bioinformatics AI Scientist will play a central role in AI-powered genomics research and data analysis, focusing on identifying novel AI solutions, training and fine-tuning GenAI models ...

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Genomic Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do genomic data scientist jobs pay per year?

As of Jul 22, 2026, the average yearly pay for genomic data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are Genomic Data Scientists?

Genomic Data Scientists are professionals who analyze and interpret large-scale genomic data using computational, statistical, and bioinformatics techniques. They work at the intersection of biology, computer science, and statistics to extract meaningful insights from genetic information. Their work supports research in areas such as personalized medicine, disease gene discovery, and evolutionary biology. Genomic Data Scientists often collaborate with researchers, clinicians, and other scientists to solve complex biological problems and advance scientific understanding.

What are some common challenges faced by Genomic Data Scientists when working with large-scale genomic datasets?

Genomic Data Scientists often encounter challenges related to managing and processing massive datasets, which require robust computational resources and efficient data storage solutions. Data integration from different sources and formats can also be complex, necessitating careful quality control and normalization. Additionally, ensuring reproducibility of analyses and translating raw data into actionable biological insights require strong collaboration with biologists, clinicians, and other data scientists. Staying updated with evolving tools, algorithms, and best practices is also essential for success in this rapidly changing field.

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

To thrive as a Genomic Data Scientist, you need expertise in bioinformatics, statistics, and genomics, typically supported by a degree in computational biology, bioinformatics, or a related field. Familiarity with programming languages like Python or R, experience with high-throughput sequencing data analysis tools, and knowledge of genomic databases are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret complex data and collaborate across disciplines. These skills are crucial for deriving actionable insights from large-scale genomic data and advancing research or clinical applications.
More about Genomic Data Scientist jobs
What cities are hiring for Genomic Data Scientist jobs? Cities with the most Genomic Data Scientist job openings:
What states have the most Genomic Data Scientist jobs? States with the most job openings for Genomic Data Scientist jobs include:
Infographic showing various Genomic Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Associate Bioinformatics Data Scientist

Associate Bioinformatics Data Scientist

Signature Science, LLC

Charlottesville, VA

$75K/yr

Full-time

Posted 22 days ago


Job description

Position Purpose:   

A bioinformatics data scientist is responsible for providing experimental design consulting and data analysis for large, high-throughput genomic experiments, with a focus on forensics and metagenomics. The bioinformatics data scientist will be responsible for designing and implementing annotated code for managing, manipulating, and analyzing large-scale genomic data, and for preparing thorough documentation and reporting.

This position is a full-time, on-site role at the Signature Science office in Charlottesville, VA.

Essential Duties and Responsibilities:

  • Develop tools for management, analysis and interpretation of high-density microarray and whole genome sequencing data.
  • Manage, manipulate, and analyze data using a combination of R, python, and UNIX tools.
  • Use established domain-specific open-source software and tools to manipulate and analyze genomic data.
  • Implement and execute data processing workflows and automated analytic pipelines.
  • ·     Apply literate‑programming methods to develop reproducible workflows that produce consistent, standardized tables and figures.
  • Conduct workflow benchmarking and documentation, identifying inconsistencies and resolving data problems.
  • Prepare SOPs, document source code/workflows, and write reports to summarize computational requirements, processing status, and customized analysis results.

Required Knowledge, Skills & Abilities:

  • Advanced proficiency working in a Unix/Linux environment.
  • Advanced proficiency with open-source software, tools, and databases for analyzing next-generation sequencing data (whole-genome sequencing, RNA-seq, epigenetics, microbiome, and metagenomics).
  • Proficiency working with and developing using Docker and/or Singularity container technology.
  • Proficiency using version Control software (e.g., Git or similar) to manage programming code.
  • Proficiency with Python, Perl, or another scripting language.
  • Proficiency with R, RMarkdown, and the "tidyverse" tools for data analysis.
  • Preferred: Experience with NextFlow, SnakeMake, or similar workflow/pipeline management systems.
  • Preferred: Familiarity with developing and querying relational databases.
  • Preferred: Familiarity with AWS and/or Azure cloud computing.

Education/Experience:

  • BA or BS in Computer Science, Bioinformatics, or related field
  • Experience managing and analyzing large-scale datasets produced sequencing platforms and delivering solutions for managing, visualizing, analyzing, and interpreting genomic data
  • Experience using Linux/Unix text processing tools, R, and other open-source tooling to manipulate and format data, to assess data quality, and analyze data.

Clearance:

  • This position requires that the candidate be willing and able to complete a successful background screening for a security clearance. Candidates with a current security clearance will receive preference.

 

Supervisory Responsibilities:

  • May serve as a bioinformatics task lead.

 

Working Conditions/ Equipment:

  • Ability to work in varying conditions to include: traditional office environments with sedentary extended periods required for code development and testing.