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Full Time Biology Data Scientist Jobs (NOW HIRING)

Legend Biotech USA, Inc.

Whether you come from a deep biological background with strong computational skills or a data ... These benefits are offered exclusively to permanent full-time employees. Contractors are not ...

LSU AgCenter

This is a full-time 12-month, tenure-track position with 80% research and 20% teaching appointment focused on computational biology/data science in the Department of Plant Pathology and Crop ...

Louisiana State University

This is a full-time 12-month, tenure-track position with 80% research and 20% teaching appointment focused on computational biology/data science in the Department of Plant Pathology and Crop ...

Louisiana Workforce Commission

This is a full-time 12-month, tenure-track position with 80% research and 20% teaching appointment focused on computational biology/data science in the Department of Plant Pathology and Crop ...

GondolaBio

Senior Biological Data Scientist

$155K - $205K/yr

... data can answer challenging scientific questions, generate therapeutic hypotheses, and advance ... PhD in Computational Biology, Bioinformatics, Genetics, or a related quantitative discipline with ...

BridgeBio Pharma

Senior Biological Data Scientist

PhD in Computational Biology, Bioinformatics, Genetics, or a related quantitative discipline with ... For BridgeBio Full-Time U.S Based Roles: Financial & Rewards * Market-leading compensation * 401(k) ...

AstraZeneca

Scientist, Data Science

Waltham, MA

Ph.D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0-2 years post-graduate experience); or MS with 2-4 years of experience; or BS with 4+ years of ...

New

AstraZeneca

Scientist, Data Science

Waltham, MA · On-site

Ph.D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0-2 years post-graduate experience); or MS with 2-4 years of experience; or BS with 4+ years of ...

New

Biohub

Staff Data Scientist, Imaging

Redwood City, CA · On-site +1

Our technology powers scientists around the world, translating AI capabilities into tools that ... The data that trains biological frontier models comes in dozens of modalities-sequences, images ...

AstraZeneca

Scientist, Data Science

Waltham, MA · On-site

Ph.D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0-2 years post-graduate experience); or MS with 2-4 years of experience; or BS with 4+ years of ...

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All JobsBiology Data Scientist JobsFull Time Biology Data Scientist Jobs

Full Time Biology Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do full time biology data scientist jobs pay per year?

As of Aug 9, 2026, the average yearly pay for full time biology 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 is the difference between Full Time Biology Data Scientist vs Full Time Bioinformatics Analyst?

AspectFull Time Biology Data ScientistFull Time Bioinformatics Analyst
Required CredentialsDegree in Biology, Data Science, or related field; experience with statistical toolsDegree in Bioinformatics, Biology, or Computer Science; proficiency in data analysis tools
Work EnvironmentResearch labs, biotech companies, pharmaceutical firmsResearch institutions, biotech companies, healthcare organizations
Industry UsageUsed for analyzing biological data, developing models, interpreting resultsFocuses on managing biological datasets, developing pipelines, and data interpretation

Both roles involve analyzing biological data, but a Full Time Biology Data Scientist emphasizes statistical modeling and data science skills, while a Full Time Bioinformatics Analyst focuses more on managing and processing biological datasets using specialized tools. The roles often overlap but differ in their primary focus and technical expertise.

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

To thrive as a Full Time Biology Data Scientist, a strong background in biology, statistics, and data analysis—often supported by an advanced degree in a related field—is essential. Proficiency with programming languages such as Python or R, experience with bioinformatics tools, and familiarity with databases and machine learning platforms are typically required. Excellent problem-solving skills, attention to detail, and the ability to communicate complex findings clearly are valuable soft skills in this role. These competencies enable effective interpretation of biological data, drive scientific discovery, and support meaningful collaboration with cross-functional teams.

What does a full time biology data scientist do?

A Full Time Biology Data Scientist analyzes large sets of biological data, such as genomic, proteomic, or clinical information, to uncover patterns and generate insights relevant to biological research or healthcare. They use statistical methods, machine learning, and programming skills to interpret complex datasets and help guide scientific decision-making. Their work often contributes to advancements in fields like drug discovery, personalized medicine, and biotechnology. They collaborate with biologists, clinicians, and other data scientists to design experiments, validate models, and communicate findings.

How does a full time biology data scientist typically collaborate with laboratory researchers and other interdisciplinary teams?

As a Full Time Biology Data Scientist, you will frequently collaborate with laboratory researchers by helping them design experiments, analyze large-scale biological data, and interpret results. You’ll also work closely with bioinformaticians, software engineers, and statisticians to develop data pipelines and ensure robust, reproducible analyses. Regular meetings and cross-functional projects are common, so strong communication skills and the ability to translate complex data insights into actionable recommendations for non-technical stakeholders are essential. This collaborative environment supports innovative, data-driven research and fosters continuous professional growth.
What cities are hiring for Full Time Biology Data Scientist jobs? Cities with the most Full Time Biology Data Scientist job openings:
What are the most commonly searched types of Biology Data Scientist jobs? The most popular types of Biology Data Scientist jobs are:
What states have the most Full Time Biology Data Scientist jobs? States with the most job openings for Full Time Biology Data Scientist jobs include:
Full Time Biology Data Scientist jobs near you

Scientist/Sr. Scientist, Bioinformatics Data

Legend Biotech US

Somerset, NJ • Hybrid

Full-time

Re-posted 23 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 

  • 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.
  • 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.
  • 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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