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Data Annotation Manager Jobs in Arizona (NOW HIRING)

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

Familiarity with cloud-based data storage (AWS S3, Google Cloud Storage, etc.) and distributed systems for managing large datasets. * Experience with data annotation tools and platforms for manual or ...

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

Familiarity with cloud-based data storage (AWS S3, Google Cloud Storage, etc.) and distributed systems for managing large datasets. * Experience with data annotation tools and platforms for manual or ...

Data Annotation

$50 - $60/hr

Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises related to finance management * A current, in progress, or completed Master's and/or PhD is ...

Data Annotation

$50 - $60/hr

Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises related to finance management * A current, in progress, or completed Master's and/or PhD is ...

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All JobsData Annotation Manager JobsData Annotation Manager Jobs in Arizona

Data Annotation Manager information

See Arizona salary details

$28.9K

$90.5K

$160.3K

How much do data annotation manager jobs pay per year?

As of Jul 6, 2026, the average yearly pay for data annotation manager in Arizona is $90,528.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,500.00 and $117,000.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a data annotation manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and familiarity with annotation tools and team management can influence pay levels.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards are met, often requiring familiarity with annotation tools and project management skills.

What are some common challenges faced by Data Annotation Managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

Does data annotation actually pay well?

Data annotation managers typically earn competitive salaries that reflect their experience and responsibilities, often ranging from entry-level to senior roles. Compensation can vary based on industry, location, and company size, with specialized skills in tools like labeling platforms and quality control often leading to higher pay.

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

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

How hard is it to get hired by data annotation?

Getting hired as a data annotation manager typically requires relevant experience in data labeling, familiarity with annotation tools, and strong organizational skills. The hiring process often involves reviewing previous work, technical assessments, and demonstrating attention to detail, with opportunities available in companies that outsource data labeling tasks.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Arizona? The most popular types of Data Annotation jobs in Arizona are:
What are popular job titles related to Data Annotation Manager jobs in Arizona? For Data Annotation Manager jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in Arizona look for? The top searched job categories for Data Annotation Manager jobs in Arizona are:
What cities in Arizona are hiring for Data Annotation Manager jobs? Cities in Arizona with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in Arizona as of June 2026, with employment types broken down into 3% As Needed, 63% Full Time, and 34% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $90,528 per year, or $43.5 per hour.
Remote FP&A Manager - AI Trainer ($50-$60 per hour)

Remote FP&A Manager - AI Trainer ($50-$60 per hour)

Data Annotation

Douglas, AZ • Remote

$50 - $60/hr

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

DataAnnotation is committed to creating high-quality AI. Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an opportunity to work with us as an independent contractor.

We're currently expanding into an exciting new area – teaching AI Assistant models to be a more useful tool for finance professionals. We're seeking experienced finance professionals with advanced degrees (MBA+) and professional experience to use their expertise to help shape how AI understands financial principles and decision-making.

In this role, you might:

  • Review and improve AI Assistant answers to questions about macro trends, corporate finance, and capital markets
  • Leverage your education and work experience to check the reasoning and accuracy of an AI Assistant's work
  • Push the models with complex, real-world scenarios and edge cases to see where their reasoning holds up – and where it doesn’t.
  • Share clear, structured feedback to help make each new version of the AI smarter and more reliable.

To succeed in this position, you should have expert-level financial reasoning and formal training in a finance-related discipline. A Master’s or PhD (completed or in progress) is strongly preferred. Relevant backgrounds include Financial Accounting, Investment Banking, Corporate Development, Wealth Management, and Insurance Planning.

Advantages of contracting with us:

  • You'll be able to choose which projects you want to work on and when
  • You work on your own schedule, on your own computer, from the comfort of your own home
  • Projects are paid hourly starting at USD $50-$60 per hour, with bonus rates available on some projects

Responsibilities:

  • Give AI chatbots diverse and complex problems and evaluate their outputs
  • Evaluate the quality produced by AI models for correctness and performance

Qualifications:

  • Fluency in English (native or bilingual level)
  • Detail-oriented
  • Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises related to finance management
  • A current, in progress, or completed Master's and/or PhD is preferred but not required

Note: Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. This is an independent contract position.

Apply