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Data Annotation Analyst Jobs (NOW HIRING)

JPMorganChase

Data Domain Architect Lead

Wilmington, DE · On-site

Responsibilities : • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis • Partner with leads in ...

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Data Annotation Analyst information

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$82.6K

$136K

How much do data annotation analyst jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data annotation analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

Is it difficult to get a job at data annotation?

Securing a data annotation analyst position generally requires attention to detail, basic understanding of data labeling tools, and sometimes prior experience or training. Entry-level roles are often accessible with minimal experience, but more advanced positions may demand specific skills or knowledge of machine learning concepts.

Does data annotation actually pay well?

Data annotation analysts typically earn entry-level wages that are often below average for tech-related roles, with pay varying based on experience, location, and the complexity of annotation tasks. While some positions offer higher pay for specialized skills or certifications, overall compensation tends to be modest compared to other data science or engineering roles.

What does a typical day look like for a Data Annotation Analyst?

As a Data Annotation Analyst, your day usually involves reviewing various data types (like images, text, or audio) and applying precise labels or tags according to specific project guidelines. You may participate in regular team meetings to clarify instructions, resolve ambiguities, and update productivity targets. Routine feedback sessions with quality assurance teams are common to ensure consistency and accuracy in the annotated data. Collaboration with data scientists or machine learning engineers might also occur to improve annotation processes or address edge cases. The work environment is typically structured, with deadlines and accuracy benchmarks guiding daily activities.

What is a data annotation analyst?

A data annotation analyst is a professional who labels and categorizes data, such as images, text, or videos, to help train machine learning models. They use tools and follow guidelines to ensure data quality and accuracy, often working with large datasets in a structured environment.

What are the key skills and qualifications needed to thrive in the Data Annotation Analyst position, and why are they important?

To excel as a Data Annotation Analyst, you need strong attention to detail, analytical abilities, and familiarity with data labeling processes, often supported by a relevant degree or experience in data handling. Proficiency with specialized annotation tools (such as Labelbox or CVAT), spreadsheet software, and sometimes scripting languages is highly valued. Excellent communication skills, adaptability, and the ability to work independently or collaboratively are crucial soft skills in this role. These skills ensure accurate, high-quality data annotations that are essential for training reliable machine learning models.

Is data annotation still hiring?

Data annotation analyst roles are currently in demand as companies continue to develop AI and machine learning models. These positions often require attention to detail, familiarity with annotation tools, and sometimes basic knowledge of data privacy standards. Opportunities are available across various industries, including technology, healthcare, and automotive sectors.

What is a Data Annotation Analyst job?

A Data Annotation Analyst is responsible for labeling, tagging, and categorizing data to help train and improve machine learning models. They work with text, images, audio, or video, ensuring that datasets are accurate and high-quality. This role requires attention to detail, consistency, and familiarity with annotation guidelines to enhance AI performance.

More about Data Annotation Analyst jobs
What cities are hiring for Data Annotation Analyst jobs? Cities with the most Data Annotation Analyst job openings:
What are the most commonly searched types of Data Annotation Analyst jobs? The most popular types of Data Annotation Analyst jobs are:
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Data Annotation Analyst jobs near you
Infographic showing various Data Annotation Analyst job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 86% Full Time, 6% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Python Developer _ MRM & Data Annotation (AI/ML)

Tata Consultancy Service Limited

Charlotte, NC • On-site

$110K - $125K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 29 days ago

Job description

Must Have Technical/Functional Skills
Python , MRM , Data Annotator ,Agile concepts, CI/CD
10+ years experience
Roles & Responsibilities
• 10+ years of hands experience in Python , MRM , Data Annotator
• Build and maintain Python pipelines for data ingestion, preprocessing, and model feature preparation.
• Implement MRM controls such as model documentation, versioning, validation evidence, and audit trails.
• Develop tools for annotation workflow automation (task assignment, QA sampling, and label consistency checks).
• Collaborate with risk, compliance, and data science teams to align model development with governance standards.
• Create reproducible training/evaluation scripts with clear experiment tracking and model lineage.
• Define and monitor model performance, drift, and data quality metrics across lifecycle stages.
• Design labeling guidelines and enforce annotation standards to improve downstream model reliability.
• Perform root-cause analysis for model errors and annotation defects, then drive corrective actions.
• Build APIs/utilities for secure data access, transformation, and integration with internal platforms.
• Support model validation activities with technical artifacts, assumptions, and testing evidence.
• Ensure adherence to data privacy, security, and responsible AI policies in all workflows.
• Document SOPs, handover notes, and technical runbooks for operational continuity.
Generic Managerial Skills, If any
• Proactive and result-oriented leader, adept in mentoring and motivating the dynamic team to exemplary performance.
• Strong communication, collaboration, and team building skills with proficiency in grasping new technical concepts quickly
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
Salary Range: $110,000-$125,000 a year

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