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Data Annotation Biology Jobs in Boston, MA (NOW HIRING)

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Data Annotation Biology information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

How much do data annotation biology jobs pay per year?

As of Aug 21, 2026, the average yearly pay for data annotation biology in Boston, MA is $133,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,800.00 per year, depending on experience, location, and employer.

What is data annotation in biology?

Data annotation in biology involves labeling or tagging biological data—such as images, gene sequences, or medical records—with relevant information to make it useful for research and machine learning. Annotators may identify specific features, mark regions of interest, or classify data according to biological characteristics. This work is crucial for training artificial intelligence systems to recognize patterns, make predictions, and automate analyses in biological research. Annotated datasets help improve the accuracy and reliability of computational models in genomics, microscopy, drug discovery, and more.

What are the unique challenges faced by data annotators working with biological datasets, and how can they be addressed?

Data annotators in biology often encounter challenges such as dealing with complex, high-dimensional data (like gene sequences or microscopy images) and the need for a deep understanding of biological terminology and context. Errors in annotation can significantly impact downstream research or machine learning models, so maintaining accuracy is crucial. Collaborating closely with biologists and domain experts helps ensure consistency and correctness, while ongoing training and clear annotation guidelines help address ambiguities. Staying up-to-date with evolving biological standards and tools is also essential for success in this role.

What are the key skills and qualifications needed to thrive as a data annotation biology specialist, and why are they important?

To thrive as a Data Annotation Biology specialist, you need a solid background in biological sciences, attention to detail, and experience handling scientific datasets, often supported by a degree in biology or a related field. Familiarity with annotation tools, bioinformatics databases, and software such as BLAST or Ensembl is typically required, alongside knowledge of data management systems. Strong analytical thinking, precision, and good communication skills help you interpret complex biological data and collaborate effectively with researchers. These skills ensure the accuracy and utility of annotated datasets, which are critical for advancing biological research and data-driven discoveries.

What is the difference between Data Annotation Biology vs Data Labeling Specialist?

AspectData Annotation BiologyData Labeling Specialist
Required CredentialsBiology degree or related certificationHigh school diploma or equivalent, training in labeling tools
Work EnvironmentLaboratory, research settings, or remoteOffice, remote, or data centers
Industry UsageBiotech, healthcare, researchTech, AI, machine learning
Job FocusAnnotating biological data, images, and sequencesLabeling various data types for AI models

Data Annotation Biology involves annotating biological data, often requiring a background in biology, while Data Labeling Specialists focus on labeling diverse data types for AI applications, with less emphasis on biological expertise. Both roles are essential in data preparation but serve different industry needs.

What are popular job titles related to Data Annotation Biology jobs in Boston, MA?

For Data Annotation Biology jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Data Annotation Biology jobs in Boston, MA look for?

The top searched job categories for Data Annotation Biology jobs in Boston, MA are:

What cities near Boston, MA are hiring for Data Annotation Biology jobs?

Cities near Boston, MA with the most Data Annotation Biology job openings:

Data Annotation Biology jobs near you
Infographic showing various Data Annotation Biology 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 $133,343 per year, or $64.1 per hour.

Data Scientist Contractor, Computational Biology

CAMP4 Therapeutics

Cambridge, MA

$64K - $64K/yr

Contractor

Re-posted 26 days ago

Job description

Position Title: Data Scientist Contractor, Computational Biology (6-month contract)
Reports To: Senior Director, Head of Data Sciences
Location: Cambridge, MA
Join the adventure!
CAMP4 is seeking a Data Science Contractor for a 6-month temporary contract assignment, specializing in Computational Biology, Bioinformatics, or Systems Biology, to support the processing, analysis, visualization, and interpretation of next-generation sequencing datasets. This assignment will have a particular focus on RNA-seq, scRNAseq, and long-read sequencing data, including Nanopore and PacBio platforms.
The successful candidate will apply state-of-the-art computational tools and, where needed, develop fit-for-purpose analytical approaches to interrogate complex genomics datasets. This role will help generate focused biological hypotheses to support target identification, target validation, and drug discovery programs. The candidate will work closely with experimental biologists and data scientists to systematically apply hypothesis-driven genomics approaches to advance CAMP4’s understanding of transcriptional mechanisms of disease and therapeutic strategies derived from them.

Key Responsibilities:
  • Process, analyze, visualize, and interpret next-generation sequencing (NGS) datasets, with an emphasis on bulk RNA-seq, scRNAseq, and long-read RNA sequencing, including Nanopore and PacBio sequencing data.
  • Execute bioinformatics analyses according to predefined analysis plans, including quality control, alignment, quantification, differential expression analysis, isoform/transcript analysis, splicing analysis, and integrative interpretation of results.
  • Collaborate closely with cross-functional teams, including experimental biologists, computational scientists, and project teams, to develop, refine, and execute research plans.
  • Provide clear biological interpretation and scientific context for computational results to support target discovery, validation, and mechanistic understanding.
  • Evaluate, implement, and apply new bioinformatics methods, tools, and emerging technologies relevant to transcriptomics, long-read sequencing, and functional genomics.
  • Develop scripts, workflows, and software tools where gaps exist to enable reproducible and scalable data analysis.
  • Provide conceptual input into analysis plans, including analytical strategy, study design, prioritization, and interpretation of key results.
  • Participate in cross-functional discussions to refine project goals, identify key priorities, and communicate findings effectively to both computational and experimental scientists.
  • Demonstrate strong ownership, attention to detail, and a sense of urgency in delivering high-quality analyses that support the discovery of breakthrough medicines for patients.
Qualifications:
Education amp; Experience
  • PhD in Bioinformatics, Computational Biology, Systems Biology, or a related field with 3+ years of relevant industry or postdoctoral experience.
Skills amp; Competencies
  • Strong hands-on experience analyzing NGS datasets, especially RNA-seq, scRNAseq, and long-read sequencing data from Nanopore and/or PacBio platforms.
  • Familiarity with long-read sequencing tools and workflows for transcript discovery, isoform characterization, or full-length transcript analysis is highly desirable.
  • Experience with additional functional genomics datasets, such as ATAC-seq, ChIP-seq, and PRO-seq.
  • Solid background in statistics and strong programming skills in Python and/or R.
  • Experience working in a Linux environment and using high-performance computing clusters and/or cloud computing platforms such as AWS.
  • Familiarity with human genome annotation resources, biological pathway databases, and systems biology concepts.
  • Strong commitment to reproducible research, best practices in software development, documentation, and version control.
  • Excellent collaboration and communication skills, with the ability to explain computational results clearly to experimental scientists and cross-functional teams.
  • Strong attention to detail, high professional integrity, and commitment to excellence in execution.
  • Creative and solution-oriented with the ability to develop fit-for-purpose approaches for diverse data and project needs.
  • Passionate about applying computational biology and genomics to translate fundamental scientific discoveries into medicines that improve patients’ lives.
Compensation:
Pay rate for this role will be determined based on the candidate’s skills and experience.

About CAMP4:
CAMP4 is developing disease-modifying treatments for a broad range of genetic diseases where amplifying healthy protein may offer therapeutic benefits. Our approach amplifies mRNA by harnessing a fundamental mechanism of how genes are controlled. To amplify mRNA, our therapeutic ASO drug candidates target regulatory RNAs (regRNAs), which act locally on transcription factors and are the master regulators of gene expression. CAMP4’s proprietary RAPTM Platform enables the mapping of regRNAs and design of optimal chemistry to generate potent therapeutic candidates to address hundreds of genetic diseases across multiple tissues. Learn more about us at www.camp4tx.com and follow us @CAMP4tx.

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