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

Bayer

Computational Biologist - Spatial Multi-Omics

Cambridge, MA · On-site

$106K - $159K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... data ingestion, QC, normalization, batch correction, feature extraction, and annotation from mass ... Required qualifications: * PhD in Computational Biology, Bioinformatics, Systems Biology ...

micro1 AI

AI Trainer - Microbiology Expert

Lynn, MA · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Lowell, MA · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

micro1 AI

AI Trainer - Microbiology Expert

Boston, MA · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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Showing results 1-20

All JobsData Annotation Biology JobsData Annotation Biology Jobs in Boston, MA

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 15, 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 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 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 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 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 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, 82% Full Time, 12% Part Time, and 5% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $133,343 per year, or $64.1 per hour.

Data Scientist - Computational Biology

Penfield Search Partners

Waltham, MA • Hybrid

$63K - $64K/yr

Full-time

Posted 26 days ago

Job description

Job Description Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com No 3rd party candidates Location: Waltham, MA (Hybrid - 4 days onsite/week) Penfield Search Partners is partnering with an innovative biotechnology company to identify a Data Scientist - Computational Biology contractor for a six-month assignment. This individual will support drug discovery research by processing, analyzing, visualizing, and interpreting next-generation sequencing (NGS) datasets, with a strong emphasis on transcriptomics and long-read sequencing technologies. The ideal candidate has hands-on experience with RNA sequencing data, strong computational biology expertise, and enjoys collaborating closely with experimental scientists to generate biological insights that advance therapeutic discovery

Key Responsibilities Process, analyze, visualize, and interpret NGS datasets, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and long-read RNA sequencing data. Perform bioinformatics analyses including quality control, sequence alignment, quantification, differential expression, isoform characterization, splicing analysis, and biological interpretation. Collaborate with cross-functional teams of experimental scientists, computational biologists, and research leaders to support target discovery and validation efforts.

Translate computational findings into meaningful biological insights that inform research decisions. Evaluate and implement new bioinformatics tools, analytical methods, and emerging technologies relevant to transcriptomics and functional genomics. Develop scripts, workflows, and analytical pipelines to support reproducible and scalable data analysis.

Contribute to study design, analytical strategy, and interpretation of research findings. Present results and communicate complex analyses clearly to technical and non-technical stakeholders. Deliver high-quality work while managing multiple priorities in a collaborative research environment.

Qualifications Education & Experience MS or PhD in Bioinformatics, Computational Biology, Systems Biology, Genomics, or a related scientific discipline. Relevant industry, academic, or postdoctoral research experience in computational biology or bioinformatics. Required Skills Hands-on experience analyzing NGS datasets, particularly: Bulk RNA-seq Single-cell RNA-seq (scRNA-seq) Long-read RNA sequencing using Nanopore (required) Experience with PacBio sequencing is a plus.

Strong understanding of transcriptomics, differential expression analysis, isoform discovery, and RNA splicing analysis. Proficiency in Python and/or R. Experience working in Linux environments and high-performance computing (HPC) or cloud platforms such as AWS.

Familiarity with genome annotation resources, biological pathway databases, and systems biology concepts. Commitment to reproducible research, documentation, and version control best practices. Preferred Experience Experience with additional functional genomics data such as ATAC-seq, ChIP-seq, or PRO-seq.

Drug discovery or biotechnology industry experience. Experience collaborating with laboratory scientists in a multidisciplinary research environment. What We're Looking For We're seeking someone who is curious, collaborative, and scientifically driven, with excellent communication skills and the ability to work closely with both computational and experimental teams.

This individual should be comfortable presenting previous research, explaining analytical approaches, and contributing to a fast-paced drug discovery environment.

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