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Senior Data Annotation Analyst Jobs (NOW HIRING)

Q ANALYSTS LLC

Data Annotation Technician

Kirkland, WA · On-site +1

Q Analysts has a sixteen-years track record of providing managed services and we've partnered with ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

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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 Jul 18, 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.

Is it difficult to get a job at data annotation?

Securing a position as a Senior Data Annotation Analyst typically requires attention to detail, familiarity with annotation tools, and basic understanding of data labeling processes. While some roles may require prior experience or specific skills, entry-level positions are often accessible with relevant training or certifications. The difficulty varies depending on the company's requirements and the competitiveness of the job market.

Does data annotation actually pay well?

Data annotation analysts typically earn hourly wages that are considered modest compared to other tech roles, with pay often ranging from minimum wage to around $15-$20 per hour depending on experience and location. While some companies offer bonuses or flexible schedules, overall compensation for entry-level data annotation positions is generally lower than more specialized data science or engineering roles.

What are Senior Data Annotation Analysts?

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 does a data annotation analyst do?

A data annotation analyst labels and categorizes data such as images, text, or videos to help train machine learning models. They use tools and guidelines to ensure data is accurately annotated, which is essential for developing reliable AI systems. Attention to detail and understanding of data formats are important in this role.

What are the key skills and qualifications needed to thrive as a Senior Data Annotation Analyst, and why are they important?

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 is the highest salary for data annotator?

The highest salary for a senior data annotation analyst can reach around $70,000 to $90,000 annually, depending on experience, location, and the complexity of annotation tasks. Advanced roles with specialized skills or certifications may offer higher compensation, especially in competitive tech markets.
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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

Data Annotation Specialist

Blackstone Talent Group

Sunnyvale, CA • On-site

$30 - $35/hr

Other

Posted 3 days ago

Job description

Data Annotation Specialist


Position Details:

Location: San Francisco, CA 94107 (Onsite)

Type: Contract

$30-35w2 per hour


The Annotation QA Specialist is responsible for ensuring the quality, accuracy, and consistency of annotated datasets. Working closely with internal teams, this role maintains high standards of data integrity and supports the smooth execution of data-related projects.


Responsibilities

  • Serve as the primary quality checkpoint for our route configuration and annotation process, ensuring adherence to quality standards and project requirements.
  • Review and evaluate datasets for accuracy, completeness, and consistency — identifying, flagging, and resolving discrepancies or errors.
  • Conduct regular quality control audits on annotated data, implementing and tracking corrective measures as needed.
  • Document QA findings and trends, providing actionable insights and recommendations to improve annotation quality over time.
  • Collaborate with annotation team members and cross-functional partners to communicate quality standards and address recurring issues.
  • Assist with data analysis and reporting tasks as needed.


Required Qualifications

  • Excellent attention to detail with a high degree of accuracy in reviewing and evaluating annotated data.
  • Strong communication and interpersonal skills, with the ability to work effectively in a team environment.
  • Ability to prioritize tasks, meet deadlines, and adapt to shifting project requirements.
  • Strong analytical and problem-solving skills, with the ability to translate data findings into actionable recommendations.
  • Proficiency in spreadsheet tools (Excel, Google Sheets).




EEO Statement:


Blackstone Talent Group is a division of Blackstone Technology Group, a global IT services and solutions firm that implements technological solutions across commercial industry verticals and the US Federal Government. Blackstone’s global talent augmentation practice was founded in 1998. Blackstone Talent Group has offices in San Francisco, Denver, Houston, Colorado Springs, and Washington, DC. We specialize in providing clients the best talent across a variety of industries and sectors.

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