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Data Annotation Biology Jobs in Baltimore, MD (NOW HIRING)

Variant calling and basic annotation and DNA methylation data processing and analysis and Data ... Biology * Proficiency in R and at least one scripting language * Experience with QC and data ...

Data Scientist 3

Annapolis, MD · On-site

$161K - $211K/yr

... annotation of language data with parts of speech information, and improve existing models by ... physics, chemistry, biology, astronomy), or other science disciplines with a substantial ...

Data Scientist 3

Annapolis, MD · On-site

$161K - $211K/yr

... annotation of language data with parts of speech information, and improve existing models by ... physics, chemistry, biology, astronomy), or other science disciplines with a substantial ...

Data Annotation Biology information

See Baltimore, MD salary details

$37.3K

$122K

$195.3K

How much do data annotation biology jobs pay per year?

As of Aug 25, 2026, the average yearly pay for data annotation biology in Baltimore, MD is $121,958.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,900.00 and $135,100.00 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 Baltimore, MD?

For Data Annotation Biology jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Data Annotation Biology jobs in Baltimore, MD look for?

The top searched job categories for Data Annotation Biology jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Data Annotation Biology jobs?

Cities near Baltimore, MD with the most Data Annotation Biology job openings:

Infographic showing various Data Annotation Biology job openings in Baltimore, MD as of August 2026, with employment types broken down into 65% Full Time, 15% Part Time, and 20% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $121,958 per year, or $58.6 per hour.

Data Scientist

Fort George G Meade, MD

Fuse Engineering LLC
IT Services • 51 - 200 employees

Full-time

Re-posted 3 days ago


Job description

Description

Support for NLP project to accurately and automatically tokenize language data with spoken or written origins; develop automated solutions for the annotation of language data with parts of speech information, and improved existing models by scoring performance against human-generated annotations for speech and text. 

Requirements

Clearance Required

Top Secret SCI w/ Full Polygraph


Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning)  and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence).  College-level requirement, or upper-level math courses designated as elementary or basic do not count. 


Must have some combination (2 or more) of the following skill areas:  

Foundations: Mathematical, Computational, Statistical

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering.