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Annotation Analyst Jobs in Maryland (NOW HIRING)

Variant calling and basic annotation and DNA methylation data processing and analysis and Data integration across datasets when directed Prepares, organizes and maintains various lab samples ...

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Annotation Analyst information

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$30.1K

$71.1K

$126.2K

How much do annotation analyst jobs pay per year?

As of Aug 18, 2026, the average yearly pay for annotation analyst in Maryland is $71,103.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,000.00 and $84,400.00 per year, depending on experience, location, and employer.

What is an annotation analyst?

An Annotation Analyst is responsible for labeling and categorizing data, such as text, images, audio, or video, to help improve machine learning models and AI systems. They follow specific guidelines to ensure accuracy and consistency in annotations. This role often involves reviewing, analyzing, and correcting data to enhance AI algorithms' performance. Annotation Analysts typically work with teams developing natural language processing (NLP), computer vision, or speech recognition technologies. Strong attention to detail and familiarity with industry tools are key skills for success in this role.

What are the typical day-to-day responsibilities of an annotation analyst?

As an Annotation Analyst, your daily responsibilities generally include reviewing and labeling large volumes of data—such as images, text, or audio—according to predefined guidelines or project requirements. You may also participate in quality control processes, address edge cases or ambiguities in the data, and collaborate with project managers, data scientists, or other analysts to ensure consistency and accuracy. Additionally, you might provide feedback on annotation tools or contribute to refining categorization criteria. The role often involves both independent work and teamwork within a fast-paced, detail-oriented environment, where precision is essential for supporting training and evaluation of AI or machine learning models.

What are the key skills and qualifications needed to thrive in the annotation analyst position, and why are they important?

To thrive as an Annotation Analyst, you need exceptional attention to detail, analytical thinking, and proficiency in data labeling or linguistic annotation, often supported by a relevant degree such as linguistics or computer science. Familiarity with annotation tools and platforms (like Labelbox, Prodigy, or proprietary systems) and knowledge of data privacy standards are highly beneficial. Strong communication, collaboration, and time management skills help in working efficiently with multidisciplinary teams and meeting project deadlines. These qualities are crucial for producing high-quality, accurate datasets that directly impact the success of machine learning and AI initiatives.

Infographic showing various Annotation Analyst job openings in Maryland as of August 2026, with employment types broken down into 87% Full Time, 8% Part Time, and 5% Contract. Highlights an 80% Physical, 9% Hybrid, and 11% Remote job distribution, with an average salary of $71,103 per year, or $34.2 per hour.

Data Scientist with Security Clearance

FUSE Engineering

Fort George G Meade, MD • On-site

Other

Re-posted 5 days ago


Job 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.