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Genomic Data Science Jobs in Houston, TX (NOW HIRING)

MD Anderson

Postdoctoral Fellow - Genomic Medicine

Houston, TX · On-site +1

$46K - $63K/yr

... of Genomic Medicine. We seek a driven and technically adept Postdoctoral Fellow to develop and ... Develop an understanding of a hands-on experience in data science analytics and model development ...

MD Anderson

Postdoctoral Fellow - Genomic Medicine

Houston, TX · On-site

$46K - $63K/yr

Being trained at the intersection between data science, genomic medicine, and drug discovery. This position will focus on establishing robust, reproducible assays suitable for compound screening and ...

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All JobsGenomic Data Science JobsGenomic Data Science Jobs in Houston, TX

Genomic Data Science information

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$14

$49

$70

How much do genomic data science jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for genomic data science in Houston, TX is $49.11, according to ZipRecruiter salary data. Most workers in this role earn between $40.29 and $58.17 per hour, depending on experience, location, and employer.

What is genomic data science?

Genomic data science is an interdisciplinary field that focuses on analyzing and interpreting vast amounts of genetic and genomic data using computational and statistical methods. Professionals in this field use bioinformatics tools, machine learning, and data analysis techniques to uncover insights about genes, diseases, evolution, and biological processes. Genomic data scientists often work with large datasets from next-generation sequencing and collaborate with biologists, clinicians, and researchers to advance our understanding of genetics and its applications in medicine and research.

How does a genomic data scientist typically collaborate with multidisciplinary teams in research or healthcare settings?

Genomic Data Scientists often work closely with biologists, clinicians, statisticians, and software engineers to interpret complex genomic datasets. Collaboration usually involves translating biological questions into analytical tasks, developing and applying computational pipelines, and communicating findings in accessible terms. Regular meetings, shared project management tools, and cross-disciplinary workshops are common, fostering an environment where diverse expertise is integrated to advance research or clinical objectives. This collaborative approach not only enhances the quality of insights but also provides opportunities for professional growth and learning from adjacent fields.

What are the key skills and qualifications needed to thrive as a genomic data scientist, and why are they important?

To excel as a Genomic Data Scientist, you need a strong background in bioinformatics, genetics, and statistical analysis, typically supported by a degree in biology, computational science, or a related field. Familiarity with tools like Python, R, next-generation sequencing (NGS) platforms, and databases such as Ensembl is crucial, as is experience with cloud computing or high-performance computing environments. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are vital soft skills in this role. These competencies enable accurate data interpretation, effective collaboration, and innovative research that advances our understanding of genomics.

What is the difference between Genomic Data Science vs Bioinformatics?

AspectGenomic Data ScienceBioinformatics
Required CredentialsDegree in Data Science, Bioinformatics, or related fields; programming skillsDegree in Bioinformatics, Biology, or related fields; computational skills
Work EnvironmentResearch labs, biotech companies, healthcare institutionsResearch labs, academic institutions, biotech firms
Industry UsageAnalyzing large genomic datasets, developing algorithmsSequence analysis, genome annotation, biological data interpretation
Common Search IntentData analysis in genomics, computational methods for geneticsGenomic sequence analysis, biological data processing

While both roles involve working with genomic data, Genomic Data Science focuses on applying data science techniques, machine learning, and statistical analysis to large genomic datasets. Bioinformatics emphasizes biological sequence analysis, genome annotation, and biological interpretation. Both fields often overlap but differ mainly in their core focus: data science methods versus biological data analysis.

What are popular job titles related to Genomic Data Science jobs in Houston, TX?

For Genomic Data Science jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Genomic Data Science jobs in Houston, TX look for?

The top searched job categories for Genomic Data Science jobs in Houston, TX are:

Genomic Data Science jobs near you
Infographic showing various Genomic Data Science job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $112,850 per year, or $54.3 per hour.

Senior Bioinformatics Software Engineer

Morpheus Group

Houston, TX • On-site

Full-time

Re-posted 8 days ago

Job description

We are seeking an experienced Senior/Staff-Level Bioinformatics Software Engineer to provide technical leadership in the design, development, and enhancement of advanced bioinformatics software solutions. This role combines software engineering, computational biology, and data science expertise to support genomic data analysis, next-generation sequencing (NGS) workflows, and the development of scalable analytical platforms.
Key Responsibilities
  • Architect and develop innovative bioinformatics applications, analytical tools, and data processing solutions.
  • Lead the creation and optimization of genomic analysis pipelines focused on sequence interpretation, variant detection, and complex biological data analysis.
  • Partner with scientists, researchers, and cross-functional stakeholders to design studies, analyze results, and translate biological requirements into software solutions.
  • Drive technical strategy and contribute to architectural decisions for current and future software platforms.
  • Improve development processes through automation, best practices, and modern engineering methodologies.
  • Mentor engineering team members and serve as a technical resource across projects. Desired Qualifications
  • Strong background in bioinformatics software development with expertise in NGS data analysis and genomic workflows.
  • Experience working with common bioinformatics formats and tools, including sequencing alignment, variant analysis, and quality control frameworks.
  • Advanced programming skills in Python, R, or similar languages used in scientific computing.
  • Proficiency with Linux environments, cloud computing platforms, and workflow orchestration tools.
  • Experience with software development best practices, source control, testing methodologies, and containerized environments.
  • Excellent communication, leadership, and collaboration skills with the ability to work effectively across scientific and technical teams.

Background
  • Bachelor's degree in Computer Science, Bioinformatics, Data Science, Statistics, Mathematics, or a related field required; advanced degrees preferred.
  • Approximately 7+ years of experience in software engineering, bioinformatics, computational biology, or a related discipline, including demonstrated technical leadership.

This opportunity is ideal for a bioinformatics professional who enjoys leading complex technical initiatives, building scalable genomics solutions, and working at the intersection of software engineering and life sciences