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Senior Data Annotation Analyst Jobs (NOW HIRING)

Alliance Credit Union

Senior Data Analyst

Lubbock, TX · On-site

$60K - $80K/yr

The Senior Data Analyst plays a critical role in advancing these efforts by transforming complex data into clear, accurate, and actionable insights that support business and operational teams.

Eden Prairie Schools

Senior Data Analyst

Eden Prairie, MN · On-site

$101K - $111K/yr

Administration/Senior Data Analyst Date Posted: 7/31/2026 Location: Administrative Services Center Date Available: 09/01/2026 Senior Data Analyst Eden Prairie School District is seeking a highly ...

Turn2Partners

Senior Data Analyst

Washington, DC · On-site

$110K - $150K/yr

Senior Data Analyst Washington, DC Metro Area (On-Site) | US Citizenship Required A growing technology organization supporting public sector clients is seeking a Senior Data Analyst to join its team.

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Senior Data Annotation Analyst information

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$55K

$99.2K

$135.5K

How much do senior data annotation analyst jobs pay per year?

As of Aug 7, 2026, the average yearly pay for senior data annotation analyst in the United States is $99,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $108,500.00 per year, depending on experience, location, and employer.

What is a senior data annotation analyst?

Senior Data Annotation Analysts are experienced professionals who oversee the process of labeling and tagging data, such as text, images, or audio, to train machine learning models. They are responsible for ensuring high-quality annotations, developing guidelines, and often mentoring junior annotators. Their work is crucial for the success of AI and machine learning projects, as accurate data annotation directly impacts model performance. Senior analysts also collaborate with data scientists and engineers to refine annotation processes and improve data quality.

What are the key skills and qualifications needed to thrive as a senior data annotation analyst?

To thrive as a Senior Data Annotation Analyst, you need expertise in data labeling, analytical thinking, and a strong understanding of machine learning concepts, often supported by a relevant degree or significant experience in data operations. Familiarity with annotation platforms (like Labelbox or Supervisely), data management tools, and quality assurance processes is typically required. Attention to detail, problem-solving, and the ability to communicate feedback effectively are crucial soft skills for this role. These competencies ensure high-quality data sets that drive accurate machine learning models and improve project outcomes.

How does a senior data annotation analyst typically collaborate with machine learning engineers and data scientists?

As a Senior Data Annotation Analyst, you will often work closely with machine learning engineers and data scientists to ensure that labeled data meets project requirements and quality standards. You may participate in meetings to discuss annotation guidelines, clarify ambiguous cases, and provide feedback on data challenges that arise. Your expertise in annotation tools and processes helps streamline workflows and ensures that the annotated datasets are reliable, which is critical for model training and evaluation. Collaboration is key, and you'll be expected to communicate effectively across teams to address issues and continuously improve the data pipeline.

What is the difference between Senior Data Annotation Analyst vs Data Annotation Specialist?

AspectSenior Data Annotation AnalystData Annotation Specialist
CredentialsBachelor's degree in related field, experience in data annotationHigh school diploma or equivalent, entry-level experience
Work EnvironmentCollaborative teams, project management, quality assuranceIndividual tasks, data labeling, basic quality checks
Industry UsageTech, AI, machine learning companiesAI startups, data labeling firms, research projects

The Senior Data Annotation Analyst typically has more experience, handles complex annotation projects, and oversees quality control, whereas the Data Annotation Specialist focuses on basic labeling tasks. Both roles are essential in AI data preparation, but the senior analyst often leads projects and ensures standards are met.

What cities are hiring for Senior Data Annotation Analyst jobs? Cities with the most Senior 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:
What states have the most Senior Data Annotation Analyst jobs? States with the most job openings for Senior Data Annotation Analyst jobs include:
Senior Data Annotation Analyst jobs near you
Infographic showing various Senior 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 $99,231 per year, or $47.7 per hour.

Data Annotation Specialist - South Bay, CA (On Site)

Welocalize

Sunnyvale, CA • On-site

Full-time

Re-posted 18 days ago

Welocalize rating

6.5

Company rating: 6.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

328th of 482 rated business services

Job description

Job Summary:
Welo Data is looking for a skilled Data Analyst to join their team and contribute to advancing AI technologies. This role offers a unique opportunity to engage directly with cutting-edge AI products, supporting the refinement and performance of machine learning models through precise data analysis and quality assurance.
Responsibilities:
• Test new AI products and provide actionable feedback to improve functionality and user experience.
• Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
• Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
• Analyze data for consistency, relevancy, and alignment with project goals.
• Perform quality control to identify and report anomalies, error patterns, and discrepancies.
• Use basic data analysis methods to extract insights and support continuous improvement.
• Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Qualifications:
Required:
• Must have valid work authorization in the US (Welocalize does not sponsor VISAs at this time).
• Test new AI products and provide actionable feedback to improve functionality and user experience.
• Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
• Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
• Analyze data for consistency, relevancy, and alignment with project goals.
• Perform quality control to identify and report anomalies, error patterns, and discrepancies.
• Use basic data analysis methods to extract insights and support continuous improvement.
• Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Preferred:
• University degree in linguistics, translation, or a related field.
• 3-5 years of professional linguistics experience.
• Strong analytical skills with the ability to detect patterns and anomalies.
• Excellent communication skills and the ability to work collaboratively in a fast-paced environment.
• Adaptability to evolving priorities and project requirements.
Company:
Welocalize provides translation supply chain management solutions that deliver market-ready, translated content. Founded in 1997, the company is headquartered in Frederick, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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