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Bioinformatics Data Analyst Jobs in Boston, MA (NOW HIRING)

AA2IT

Bioinformatics Scientist - II

Cambridge, MA · On-site

$75/hr

Senior Bioinformatics Scientist Location: Cambridge, MA Pay Rate: $75/HR - 100/HR Must Have ... Experience: * 5+ years of hands-on experience in multi-omics data analysis and integration.

MyGradJob

BIOINFORMATICS SCIENTIST

Woburn, MA

Company Description Qualifications * BS/MS in computer science, bioinformatics, or related field * 1+ year(s) experience analyzing next-generation sequencing data * Recent coding experience with a ...

Massgeneralbrigham

Bioinformatician I

Somerville, MA · On-site

$75K - $109K/yr

... bioinformatics infrastructure needed for the wide range of data collection, transformation of data, and analysis requirements that will integrate across a wide range of skills and techniques. The ...

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$7

$49

$89

How much do bioinformatics data analyst jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for bioinformatics data analyst in Boston, MA is $49.78, according to ZipRecruiter salary data. Most workers in this role earn between $39.18 and $53.27 per hour, depending on experience, location, and employer.

What is a bioinformatics data analyst?

Bioinformatics Data Analysts are professionals who use computational tools and methods to analyze biological data, such as genomic sequences or protein structures. They work at the intersection of biology, computer science, and statistics to interpret complex datasets and draw meaningful insights for research or clinical applications. Their work supports areas like drug discovery, personalized medicine, and evolutionary biology. Typically, they collaborate with biologists, software engineers, and statisticians to solve complex biological problems. Strong analytical skills and proficiency with data analysis software are essential for this role.

How do bioinformatics data analysts collaborate with researchers and other team members?

Bioinformatics Data Analysts often work closely with biologists, clinicians, and software engineers, acting as a bridge between experimental research and computational analysis. Collaboration usually involves interpreting experimental data, discussing analytical approaches, and presenting findings in a way that's accessible to non-technical stakeholders. Regular team meetings and project updates are common, and strong communication skills are essential for translating complex data insights into actionable information for the broader research team. This multidisciplinary teamwork fosters innovation and ensures that analyses align with the goals of larger research projects.

What are the key skills and qualifications needed to thrive as a bioinformatics data analyst?

To thrive as a Bioinformatics Data Analyst, a solid background in biology, statistics, and programming (often with a degree in bioinformatics, computational biology, or a related field) is essential. Proficiency with tools such as R, Python, SQL, and bioinformatics software like BLAST or Bioconductor, as well as experience with large datasets and relevant certifications, is typically required. Strong analytical thinking, attention to detail, and effective communication skills help analysts interpret complex data and collaborate with interdisciplinary teams. These skills ensure accurate data analysis, meaningful biological insights, and successful project outcomes in research or clinical settings.

What is the difference between Bioinformatics Data Analyst vs Bioinformatics Scientist?

AspectBioinformatics Data AnalystBioinformatics Scientist
Required CredentialsBachelor's or Master's in Bioinformatics, Biology, or related fieldsMaster's or PhD in Bioinformatics, Computational Biology, or related fields
Work EnvironmentData analysis teams, research labs, healthcare settingsResearch projects, development of algorithms, scientific publications
Employer & Industry UsageBiotech companies, healthcare institutions, research organizationsAcademic institutions, biotech firms, pharmaceutical companies
Common Search & ComparisonOften compared for data analysis roles in bioinformaticsMore research-focused, involved in algorithm development

Bioinformatics Data Analysts primarily focus on analyzing biological data using existing tools, while Bioinformatics Scientists develop new algorithms and conduct research. Both roles require strong computational skills, but the Scientist role typically involves more advanced research and innovation.

What are popular job titles related to Bioinformatics Data Analyst jobs in Boston, MA?

For Bioinformatics Data Analyst jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Bioinformatics Data Analyst jobs in Boston, MA look for?

The top searched job categories for Bioinformatics Data Analyst jobs in Boston, MA are:

What cities near Boston, MA are hiring for Bioinformatics Data Analyst jobs?

Cities near Boston, MA with the most Bioinformatics Data Analyst job openings:

Bioinformatics Data Analyst jobs near you
Infographic showing various Bioinformatics Data Analyst job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $103,542 per year, or $49.8 per hour.

Bioinformatics Scientist - II

AA2IT

Cambridge, MA • On-site

$75/hr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Senior Bioinformatics Scientist

Location: Cambridge, MA

Pay Rate: $75/HR - 100/HR

Must Have

Education:

  • Ph.D. in Computational Biology or closely related field — no BS/MS-only candidates will be considered.

Experience:

  • 5+ years of hands-on experience in multi-omics data analysis and integration.
  • Proven work with RNA-Seq, single-cell RNA-Seq, genotype data, spatial transcriptomics, and proteomics (e.g., OLINK).

Technical Skills:

  • Strong programming skills in R, Python, and Bash.
  • Experience with HPC systems and AWS Cloud (IAM, S3, etc.).
  • Experience working with tools like STAR, DESeq2, Seurat, scanpy, LeafCutter, etc.

Data Integration:

  • Able to combine various omics data types (gene/protein expression, mRNA splicing, spatial transcriptomics, genotype).

Communication & Collaboration:

  • Strong written/verbal communication.
  • Self-motivated, adaptable, able to juggle multiple priorities in a dynamic setting.

Nice-to-Have (Preferred Qualifications)

  • Experience with real-world data (e.g., patient-derived data, EHR-linked datasets).
  • Familiarity with spatial transcriptomics analysis tools like squidpy, MERFISH, Slide-seq.
  • Background in statistical or population genetics.
  • Multi-omics data integration (especially RNA-Seq, single-cell RNA-Seq).
  • Strong hands-on coding ability in R and Bash.
  • High-performance computing and cloud (especially AWS).

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