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Data Annotation Manager Jobs in Texas (NOW HIRING)

$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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Data Annotation Manager information

See Texas salary details

$28.9K

$90.5K

$160.2K

How much do data annotation manager jobs pay per year?

As of Jun 14, 2026, the average yearly pay for data annotation manager in Texas is $90,505.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,500.00 and $116,900.00 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 proficiency with annotation tools and team management can influence pay levels.

Is data annotation high paying?

Data annotation managers typically earn higher salaries than entry-level annotators due to their supervisory responsibilities and expertise in labeling tools and processes. Salaries vary based on experience, location, and company size, but the role generally offers competitive pay within the data labeling industry.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation managers oversee this work, ensuring accuracy and quality using tools like labeling platforms and quality control procedures.

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.

Is it hard to get a job with data annotation?

Securing a job as a data annotation manager typically requires experience in data labeling, familiarity with annotation tools, and understanding of data quality standards. While entry-level roles may be accessible with basic skills, advancing to managerial positions often demands relevant experience and leadership abilities.

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.

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 Texas? The most popular types of Data Annotation jobs in Texas are:
What cities in Texas are hiring for Data Annotation Manager jobs? Cities in Texas with the most Data Annotation Manager job openings:
Infographic showing various Data Annotation Manager job openings in Texas as of June 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $90,505 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

Laredo, TX โ€ข Remote

$50 - $60/hr

Other

Posted 6 days ago


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.

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We're currently expanding into an exciting new area โ€“ 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.

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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 โ€“ and where it doesnโ€™t.

  • Share clear, structured feedback to help make each new version of the AI smarter and more reliable.

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

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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

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Responsibilities:

  • Give AI chatbots diverse and complex problems and evaluate their outputs

  • Evaluate the quality produced by AI models for correctness and performance

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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

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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.