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Biological Data Science Jobs (NOW HIRING)

LSU AgCenter

Assistant/Associate Professor (Computational Biology/Data Science) Position Type:Faculty Department:LSUAG PL1 - Department of Plant Pathology and Crop Physiology (Lawrence E Datnoff (00013100)) Work ...

Louisiana State University

Assistant/Associate Professor (Computational Biology/Data Science) Position Type:Faculty Department:LSUAG PL1 - Department of Plant Pathology and Crop Physiology (Lawrence E Datnoff (00013100)) Work ...

Louisiana Workforce Commission

Assistant/Associate Professor (Computational Biology/Data Science) Position Type:Faculty Department:LSUAG PL1 - Department of Plant Pathology and Crop Physiology (Lawrence E Datnoff (00013100)) Work ...

Arcadia Science

Quantitative Biologist

Emeryville, CA · On-site +1

$150K - $200K/yr

... to scientists with diverse backgrounds. They have hands-on bench experience, generating biological data themselves and understanding the experimental realities that shape what analysis is even ...

Arcadia Science

Quantitative Biologist

Emeryville, CA · On-site +1

$150K - $200K/yr

... to scientists with diverse backgrounds. They have hands-on bench experience, generating biological data themselves and understanding the experimental realities that shape what analysis is even ...

Arcadia Science

Quantitative Biologist

Emeryville, CA · On-site

$150K - $200K/yr

... to scientists with diverse backgrounds. They have hands-on bench experience, generating biological data themselves and understanding the experimental realities that shape what analysis is even ...

Formation Bio

Principal Data Scientist

New York, NY

$204K - $267K/yr

You'll work at the intersection of computational biology, machine learning, and drug development ... Lead and execute complex data science projects that directly advance our drug development portfolio

LuckyJay Consulting

As an integral member of the Data Science & Bioinformatics Team, you will tackle some of the most interesting biological and technical questions related to functional precision cancer therapeutics.

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Biological Data Science information

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$32.5K

$47.3K

$70K

How much do biological data science jobs pay per year?

As of Jul 24, 2026, the average yearly pay for biological data science in the United States is $47,326.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,500.00 and $52,000.00 per year, depending on experience, location, and employer.

What biology jobs pay over $100k?

Biological data science roles such as senior bioinformatician, computational biologist, and data scientist often pay over $100,000 annually, especially with advanced skills in programming, statistical analysis, and experience with tools like R or Python. Positions in biotech, pharmaceutical companies, or research institutions tend to offer higher salaries for those with specialized expertise and advanced degrees.

What careers can you do with biological science?

Biological Data Science professionals can pursue careers in research, healthcare, biotechnology, pharmaceuticals, and environmental science. They analyze biological data using tools like statistical software and programming languages such as Python or R, often working in labs, research institutions, or industry settings.

How much do biological data scientists make?

Biological data scientists typically earn a median salary ranging from $80,000 to $120,000 annually, depending on experience, education, and location. Advanced skills in bioinformatics tools, programming languages like Python or R, and knowledge of biological sciences can influence earning potential.

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

To thrive as a Biological Data Scientist, you need a strong background in biology, statistics, and data analysis, often supported by an advanced degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience with bioinformatics tools (e.g., BLAST, Bioconductor), and knowledge of databases such as GenBank are typically required. Strong problem-solving, collaboration, and communication skills help you interpret complex data and effectively share findings with interdisciplinary teams. These skills are crucial for deriving meaningful biological insights from large datasets and driving innovation in research or healthcare.

What does a biological data scientist do?

A biological data scientist analyzes biological data, such as genomic, proteomic, or clinical datasets, using statistical and computational methods. They develop algorithms, build models, and use tools like R or Python to interpret complex biological information, often working in research or healthcare environments to support scientific discoveries and decision-making.

What is Biological Data Science?

Biological Data Science is an interdisciplinary field that combines biology, computer science, statistics, and mathematics to analyze and interpret complex biological data. Professionals in this field work with large datasets generated from genomics, proteomics, and other biological experiments to uncover meaningful patterns and insights. They use computational tools and algorithms to advance research in areas such as medicine, agriculture, and environmental science. The goal is to translate raw biological data into actionable knowledge that can drive scientific discovery and innovation.

What are some common challenges faced by professionals in Biological Data Science, and how can they be addressed?

Professionals in Biological Data Science often encounter challenges such as managing large and complex datasets, integrating diverse data types (e.g., genomics, proteomics, clinical data), and staying current with rapidly evolving analytical tools. Addressing these challenges typically involves strong collaboration with interdisciplinary teams, continuous learning of new computational methods, and implementing robust data management practices. Building effective communication skills is also important, as conveying complex findings to non-specialist stakeholders is a frequent part of the role.

What is the difference between Biological Data Science vs Bioinformatics?

AspectBiological Data ScienceBioinformatics
Required CredentialsDegree in Data Science, Biology, or related fields; programming skillsDegree in Bioinformatics, Biology, or related fields; computational skills
Work EnvironmentResearch labs, biotech companies, healthcareResearch labs, healthcare, academic institutions
Employer & Industry UsageTech companies, pharmaceuticals, research institutionsAcademic, healthcare, biotech firms
Common Search & ComparisonYesYes

Biological Data Science focuses on analyzing biological data using advanced data analytics, machine learning, and statistical methods. Bioinformatics emphasizes developing algorithms and software for understanding biological data, often with a stronger focus on computational biology. While both roles require programming skills and biological knowledge, Biological Data Science is more data analytics-oriented, whereas Bioinformatics centers on computational tool development.

More about Biological Data Science jobs
What cities are hiring for Biological Data Science jobs? Cities with the most Biological Data Science job openings:
What are the most commonly searched types of Biological Data Science jobs? The most popular types of Biological Data Science jobs are:
What states have the most Biological Data Science jobs? States with the most job openings for Biological Data Science jobs include:
Biological Data Science jobs near you
Infographic showing various Biological Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 87% Full Time, 11% Part Time, and 1% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $47,326 per year, or $22.8 per hour.
Computational Data Scientist II

Computational Data Scientist II

University of Pittsburgh

Pittsburgh, PA • On-site

Full-time

Posted 3 days ago

Job description

The Bioinformatics Core within the Division of Health Informatics at UPMC Children's Hospital of Pittsburgh is seeking a computational biologist or data scientist to develop and apply machine learning and deep learning methods for omics-driven biomedical research. This individual will work closely with faculty and collaborators across multiple pediatric research programs to support biologically grounded, translationally relevant research. Equivalent relevant work experience may be substituted for degree requirement. This position is located at UPMC Children's Hospital of Pittsburgh in Lawrenceville. PA Child Abuse History Clearance, PA State Police Criminal Record Check, and FBI Criminal Record Check will be required prior to the start of employment. Also, a current TB test will be required as a condition of employment. EEO/AA/M/F/Vets/Disabled.
Minimum Qualifications
Applicants should have an MS or PhD in computational biology, bioinformatics, computer science, statistics, data science, biomedical informatics, or a related quantitative field.
The successful candidate should have strong programming skills in Python and/or R, with experience using libraries such as PyTorch, TensorFlow, scikit-learn, or comparable tools. Experience in applying computational or statistical modeling to biomedical or biological datasets is expected.
Prior experience working with single-cell, spatial omics, or related high-dimensional omics datasets is highly desirable. Candidates should be strong critical thinkers who can translate ideas into completed analyses, models, or tools; manage contributions across multiple collaborative research projects; work independently and as part of multidisciplinary teams; and demonstrate strong oral and written communication skills.
Preferred qualifications include:
• Demonstrated experience designing and implementing models for high-dimensional biological data, beyond routine application of existing analysis pipelines.
• Hands-on experience with graph neural networks or perturbation modeling.
• Experience integrating omics data with clinical data sources such as electronic health records (EHR).
• Evidence of independent technical contribution, such as first-author or co-author publications, preprints, conference presentations, open-source software, deployed tools, analytical pipelines, or a relevant project portfolio.

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