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Nih Data Science Jobs (NOW HIRING)

Axle

AI/ML Scientist/Developer

Bethesda, MD

... and data science applications to research centers and healthcare organizations nationally and ... The Standardized Organoid Model Center is an NIH-funded initiative dedicated to advancing organoid ...

Axle

AI/ML Scientist/Developer

Bethesda, MD

$100K - $130K/yr

... and data science applications to research centers and healthcare organizations nationally and ... The Standardized Organoid Model Center is an NIH-funded initiative dedicated to advancing organoid ...

Axle

AI/ML Scientist/Developer

Bethesda, MD · On-site

$100K - $130K/yr

... and data science applications to research centers and healthcare organizations nationally and ... The Standardized Organoid Model Center is an NIH-funded initiative dedicated to advancing organoid ...

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NIH Data Science information

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$122.7K

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How much do nih data science jobs pay per year?

As of Aug 8, 2026, the average yearly pay for nih data science 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 is an NIH Data Science?

An NIH Data Science job involves managing, analyzing, and interpreting complex biomedical and health data to support scientific research and policy decisions. Professionals in this field work with big data, machine learning, and computational tools to advance medical discoveries and improve public health outcomes. They may collaborate with researchers, develop data infrastructure, and ensure data privacy and security. These roles exist across various NIH institutes and centers, supporting data-driven decision-making in health sciences.

What are the key skills and qualifications needed to thrive in the NIH Data Science position?

To thrive as an NIH Data Science professional, you need a strong background in statistics, bioinformatics, and data analysis, typically supported by a degree in a related field such as computer science, mathematics, or public health. Experience with programming languages like Python or R, familiarity with data visualization tools, and knowledge of database management systems are crucial, and certifications in data science or informatics can be advantageous. Strong problem-solving abilities, teamwork, and effective communication skills set exceptional candidates apart. These competencies are vital for extracting meaningful insights from complex biomedical datasets, supporting impactful research, and collaborating across multidisciplinary teams at the NIH.

What does an NIH Data Science do?

Data Science professionals at the NIH often work on projects involving the cleaning, analysis, and interpretation of large-scale biomedical datasets to support research or public health initiatives. Daily work may include designing and implementing algorithms, developing predictive models, and visualizing results to make data-driven recommendations. Collaboration is frequent, with data scientists working alongside researchers, clinicians, and IT specialists to tackle complex scientific questions. Professionals in this role also stay updated with emerging analytical tools and methods, contributing to continuous improvement of research practices. This dynamic environment offers opportunities to advance scientific discovery and develop expertise in high-impact areas of biomedical research.

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NIH Data Science jobs near you
Infographic showing various Nih Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% 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.

Bioinformatics/Data Scientist

Nextonic Solutions LLC

Frederick, MD

$100K - $185K/yr

Full-time

Posted 23 days ago

Job description

Nextonic Solutions is seeking a Bioinformatics/Data Scientist to join our vibrant team at the National Institutes of Health (NIH) supporting the Standardized Organoid Model Center in Frederick, MD. The Standardized Organoid Model Center is an NIH-funded initiative dedicated to advancing organoid research through the development of validated, reproducible, and well-characterized organoid models. The center brings together interdisciplinary teams of researchers to establish standardized protocols, develop quality control measures, and create resources that will benefit the broader organoid research community.


Overview


The Bioinformatics/Data Scientist will conduct comprehensive analyses of multi-omics data generated from organoid systems and corresponding normal tissues. This position is central to the SOM Center's research objectives, focusing on characterizing organoid fidelity, identifying biomarkers of successful differentiation, and developing computational frameworks for organoid quality assessment.


Responsibilities


  • The successful candidate will analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from various organoid systems and their tissue counterparts.
  • The position will develop and implement computational pipelines for data processing, quality control, and statistical analysis.
  • A major component of the role involves integrating SOM-generated data with publicly available datasets to benchmark organoid characteristics against normal tissue profiles.
  • The position requires close collaboration with experimental teams to interpret results and guide protocol optimization, as well as contributing to manuscript preparation and presenting findings at scientific conferences.


Qualifications

  • Candidates must hold a PhD in bioinformatics, computational biology, biostatistics, or a related quantitative field.
  • Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or similar platforms, is essential.
  • Strong programming skills in R and Python are required, along with experience in statistical analysis and data visualization.
  • Knowledge of proteomics and metabolomics data analysis workflows is necessary.


Preferred Qualifications


  • Previous experience analyzing organoid datasets is strongly preferred.
  • Experience with machine learning approaches for biological data, familiarity with pathway analysis tools, and knowledge of developmental biology principles will be considered valuable assets.
  • Experience with high-performance computing environments and version control systems is desirable.