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Biological Data Science Jobs (NOW HIRING)

Legend Biotech USA, Inc.

Whether you come from a deep biological background with strong computational skills or a data science background with a proven track record in working with biological data, you will play a critical ...

Formation Bio

Director, Data Science

Boston, NY

$235K - $307K/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

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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.

Scientist/Sr. Scientist, Bioinformatics Data

Legend Biotech US

Somerset, NJ • Hybrid

Other

Posted 8 days ago

Job description

Legend Biotech is seeking a Scientist/Sr. Scientist, Bioinformatics Data as part of the Early Drug Development team based in Somerset, NJ.

Role Overview

We are seeking a highly motivated, passionate, and driven Bioinformatics Data Scientist with high scientific curiosity to join our research and development team. In this role, you will bridge the gap between complex biological datasets and actionable therapeutic insights. You will design, develop, and execute scalable computational pipelines to analyze high-dimensional genomic data.The ideal candidate possesses a deep curiosity for biological systems, an analytical mindset, and the technical skillset to tackle unstructured, diverse and complex multiomics challenges. Whether you come from a deep biological background with strong computational skills or a data science background with a proven track record in working with biological data, you will play a critical role in accelerating both our discovery and clinical pipeline.

Key Responsibilities

  • Data Analysis:
    • Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq, WES/WGS, epigenetic, or multi-omics data) to identify biomarkers, therapeutic targets, or disease mechanisms.
    • Apply advanced statistical, machine learning, and data-mining techniques to extract meaningful patterns from noisy biological data.
    • Perform quality control, normalization, and batch-correction across heterogeneous datasets.
  • Pipeline Development & Automation: 
    • Design, optimize, and maintain robust, scalable bioinformatics pipelines.
    • Implement version-controlled code architectures to ensure reproducibility and scalability of data analyses.
    • Procure and integrate existing biological databases with internal datasets.
  • Cross-Functional Collaboration:
    • Translate complex computational and statistical findings into clear biological narratives for experimental biologists, clinicians, and stakeholders.
    • Collaborate with IT and other functional groups.

Requirements

  •  Ph.D. or M.S. in Bioinformatics, Computational Biology, Data Science, Genomics, Biology, or a highly quantitative field.
  • Proven experience handling genomic data (Next-Generation Sequencing/NGS data analysis is required).
  • Ability to turn raw biological data into structured insights.
  •  Strong experience with AI application in data science.
  • Advanced proficiency in R (e.g., Bioconductor, Tidyverse) and/or Python (e.g., Pandas, NumPy, Scikit-learn).
  • Experience with standard bioinformatics tools (e.g., alignment tools, variant callers, single-cell toolkits like Seurat/Scanpy).
  • Experience with cloud computing platforms (AWS, GCP) and containerization (Docker, Singularity) is a strong plus.
  • A self-starting attitude with an intrinsic desire to stay ahead of the curve in emerging computational methods and biological technologies.
  • Proven ability to thrive in a fast-paced environment, manage multiple projects simultaneously, and pivot quickly based on data-driven feedback.
  • Exceptional critical thinking skills with a knack for debugging complex code and parsing unstructured data formats.
  • Creative, innovative and excellent communication and presentation skills.
  • This role is designed as the starting point of group effort to solve complex biological and clinical problems in a fast paced environment. We look for individuals who take extreme ownership of their expertise and training, and driven by the prospect of turning data into information, and information into knowledge.

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