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Biology Data Science Jobs (NOW HIRING)

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Biology Data Science information

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$37.5K

$122.7K

$196.5K

How much do biology data science jobs pay per year?

As of Jul 23, 2026, the average yearly pay for biology 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 a Biology Data Science job?

A Biology Data Science job involves applying data analysis, machine learning, and computational techniques to biological data. Professionals in this field work with large datasets from genomics, proteomics, ecology, or clinical studies to extract insights and drive scientific discoveries. They often use programming languages like Python or R, along with statistical and bioinformatics tools, to analyze complex biological systems. These roles exist in academia, pharmaceuticals, biotechnology, and healthcare.

What are the key skills and qualifications needed to thrive in the Biology Data Science position, and why are they important?

To excel in Biology Data Science, a strong background in biological sciences paired with expertise in statistical analysis, programming (commonly Python or R), and data interpretation is essential. Familiarity with tools such as bioinformatics platforms, machine learning libraries, and data visualization software, along with relevant certifications in data science or computational biology, is highly valuable. Strong problem-solving skills, attention to detail, and effective communication abilities help you collaborate with multidisciplinary teams and present complex findings clearly. These competencies allow professionals to manage and analyze large biological datasets, driving data-driven discoveries and innovation in research or industry settings.

What are common day-to-day responsibilities for professionals in a Biology Data Science role?

Professionals in Biology Data Science typically spend their days acquiring, cleaning, and analyzing large sets of biological data, such as genomic sequences or clinical trial results. They use coding and statistical methods to uncover patterns, develop predictive models, and generate insights to support scientific discoveries or healthcare decisions. Collaboration is frequent, often requiring close coordination with biologists, clinicians, and software engineers to interpret data and ensure research objectives are met. Additionally, clear and concise reporting of findings, often through visualizations or presentations, is a regular part of the job. This blend of data science and biology offers dynamic workdays that can have a direct impact on advancing scientific knowledge and improving patient outcomes.

More about Biology Data Science jobs
What cities are hiring for Biology Data Science jobs? Cities with the most Biology Data Science job openings:
What are the most commonly searched types of Biology Data Science jobs? The most popular types of Biology Data Science jobs are:
What states have the most Biology Data Science jobs? States with the most job openings for Biology Data Science jobs include:
Infographic showing various Biology Data Science job openings in the United States as of July 2026, with employment types broken down into 72% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 78% Physical, 2% Hybrid, and 20% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Senior Scientist I, Data Science

Sail Biomedicines

Cambridge, MA • On-site

$130K - $170K/yr

Other

Posted 21 days ago


Job description

The Position 

Join our team and drive the future of programmable eRNATM therapeutics and In Vivo CAR-T therapies- where AI-driven biology, targeted delivery systems and next-generation immunotherapy converge to redefine what's possible for patients. As a key member of the Sail Biomedicines Data Science team, the Senior Scientist I will operate at the interface of platform and program, applying data-driven approaches to champion broad platform efforts and hands-on analysis of preclinical datasets to transform the treatment landscape for autoimmune diseases, and beyond. 

The ideal candidate will combine strong biological insight with quantitative rigor, applying data-driven approaches to extract actionable understanding from complex preclinical and platform datasets while helping establish scalable computational foundations for future discovery efforts. In addition to supporting in vivo CAR immunology programs, this role will contribute to emerging capabilities in systems modeling, computational protein design, molecular modeling, and AI/ML-enabled therapeutic engineering. 

Partnering closely with experimental scientists, you will spearhead efforts to translate platform and program data into actionable understanding of biology, enabling rapid iteration across our therapeutic learning cycle. 

Responsibilities 

  • Perform in-depth analysis of preclinical and platform datasets, including immunophenotyping, functional assays, and multi-omics data to support both therapeutic programs and platform development
  • Integrate and interpret data across studies and contexts to generate biological insights that inform CAR activity, persistence, immune dynamics and platform-level understanding of our therapeutics
  • Collaborate closely with immunology and platform teams to inform experimental design and interpret results 
  • Work resourcefully with internal/external datasets to contextualize findings and strengthen conclusions
  • Apply statistical and systems modeling to develop deeper understanding of product and platform attributes and performance. 
  • Apply and promote best practices in data structuring, annotation, and metadata usage to enable reliable, scalable and reusable downstream analysis across programs and platform efforts
  • Develop and maintain reproducible analysis workflows, with clear documentation and version control (Git) and contribute to a well-organized data environment by following FAIR-aligned practices in day-to-day work 
  • Communicate findings clearly with collaborators through visualizations, presentations, and written summaries 

Qualifications 

Required: 

  • Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics or related field 
  • 3+ years of experience analyzing multifaceted biological datasets in biotech, pharma, or academia 
  • Firsthand experience working in CAR-T or RNA therapeutics.
  • Demonstrated experience applying modeling (statistical, system) to biological data.  
  • Strong expertise in high-dimensional data analysis (e.g., RNA-seq, single-cell, in vivo studies) with the ability to transform raw data to refined downstream biological interpretations
  • Proficiency in Python and/or R, with strong data analysis and visualization skills and a firm grasp of modern statistics (mixed models, Bayesian methods, etc.)
  • Experience building reproducible and well-documented analysis workflows (Nextflow, Snakemake) and applying sound data organization and metadata practices
  • Demonstrated ability to champion cross-functional efforts in close collaboration with experimental scientists, taking ownership and driving insights even in areas outside your core subject matter expertise 

Preferred: 

  • Computational design of Antibody/VHH/scFv/CAR proteins
  • Experience in immunology, cell therapy, or CAR biology, particularly in vivo systems 
  • Experience integrating complex datasets and cross-study meta-analysis 
  • Exposure to cloud-based or collaborative data environments
  • Track record of impactful scientific contributions (publications or program support)  

About Sail Biomedicines 

Sail Biomedicines is building a new class of fully programmable medicines by integrating circular RNA (eRNA), targeted nanoparticle delivery, and advanced computational approaches. Our platform enables the systematic design and optimization of therapies, unlocking new possibilities across immunology and beyond. 

Salary Range: $130,000 - $170,000

Sail Biomedicines is an Equal Opportunity Employer. Sail does not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, national origin, veteran status, or any other status protected under federal, state, or local law.