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Data Annotation Project Manager Jobs in Columbus, OH

Data Center Project Manager

Columbus, OH · On-site

$116K/yr

Project Manager - Data Center Construction At Black Box , we're not just building infrastructure- we're shaping the digital backbone of the future . As a Data Center Project Manager , you will be at ...

As a Data Center Project Manager , you will be at the forefront of one of the most transformative infrastructure programs in the country: constructing the largest data center in the United States

As a Data Center Project Manager , you will be at the forefront of one of the most transformative infrastructure programs in the country: constructing the largest data center in the United States

As a Data Center Project Manager , you will be at the forefront of one of the most transformative infrastructure programs in the country: constructing the largest data center in the United States

... Data center support experience. • Infrastructure data platform experience. • Experience ... managing data-related projects. Methodology & Tools: • Strong Jira experience is required. • ...

New

Project Manager

Columbus, OH · On-site

$90 - $100/hr

Strong ability to analyze data and information with excellent project management skills. * Applicant must have excellent communications skills, ability to track, forecast and lead a team of ...

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Data Annotation Project Manager information

See Columbus, OH salary details

$16

$55

$77

How much do data annotation project manager jobs pay per hour?

As of Jul 28, 2026, the average hourly pay for data annotation project manager in Columbus, OH is $55.55, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $65.00 per hour, depending on experience, location, and employer.

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 using tools like labeling platforms and project management software.

Does data annotation actually pay?

Data annotation project managers oversee tasks where annotators are paid for labeling data used in machine learning. The pay for annotators varies depending on the platform, project complexity, and experience, with many earning hourly wages or per-task rates. The role of a project manager involves coordinating these efforts and ensuring quality, often with a salary or contract-based compensation.

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

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

How hard is it to get hired by data annotation?

Getting hired as a data annotation project manager typically requires relevant experience in project management, familiarity with annotation tools, and strong organizational skills. The role often involves coordinating teams and ensuring quality standards, with some positions requiring certifications or prior experience in data labeling environments. Competition varies depending on the company and location, but demonstrating technical knowledge and management ability can improve chances of hiring.

What is the salary of data annotation manager?

The salary of a Data Annotation Project Manager typically ranges from $60,000 to $100,000 annually, depending on experience, location, and company size. They often oversee teams using annotation tools and ensure quality standards are met in data labeling projects.

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

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

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

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What is a Data Annotation Project Manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.
What are popular job titles related to Data Annotation Project Manager jobs in Columbus, OH? For Data Annotation Project Manager jobs in Columbus, OH, the most frequently searched job titles are:
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Data and Analytics - Data Annotation

Data and Analytics - Data Annotation

J.P. Morgan

Columbus, OH • On-site

Full-time

Medical, Retirement

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


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Working at Chase means making a real difference every day for your customers, your community and
yourself. How? By putting others first, doing what's right and creating solutions that make lives better.
Build your career on our strong foundation and help shape what's nextâfor you and for us. Chase, a
leading provider of diverse financial services worldwide, is actively seeking service-center team
members to create lifelong engaged relationships with our customers by delivering superior service and
quality with every customer interaction

As a Data Domain Architect Analyst within Consumer and Community Banking, you will leverage your business expertise and knowledge of JPMorgan Chase products to collaborate effectively with Data Science, Analytics, and Engineering teams. You will be responsible for developing and enhancing machine learning solutions by gathering, curating, annotating, enriching, and validating data. Additionally, you will create taxonomies and other resources to train machine learning models, extract insights, conduct analysis, and potentially generate content.

Job Responsibilities:

  • Label and annotate call center transcripts and other datasets to support the development of machine learning models.
  • Review and validate the outputs of AI and ML models, ensuring accuracy as well as alignment with business goals and compliance standards.
  • Leverage GenAI tools to conduct deep dives into call datasets to uncover opportunities to improve customer experience.
  • Provide expert guidance to stakeholders on leveraging ML/AI discovery tools for actionable insights. 
  • Draft and refine taxonomies and classification schemas to enhance data organization and model training.
  • Identify and escalate anomalies, errors, or unexpected model behaviors, acting as a critical checkpoint in our AI workflow.
  • Work closely with data scientists, engineers, and business stakeholders to continuously improve annotation processes and model performance.

Required qualifications, capabilities, and skills:

  • Experience with banking products and/or customer service within the financial services industry
  • Bachelor's degree in business or comparable discipline; or equivalent level demonstrated in relevant work experience.
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience in working with and analyzing large real-world datasets.
  • Ability to interpret and apply business context to technical tasks.
  • Interest in machine learning and willingness to develop new skills in this area.

Preferred qualifications, capabilities, and skills

  • Prior experience with data annotation, conversational analysis, taxonomy development, machine learning projects, and/or quality assurance
  • Familiarity with industry annotation and labeling methods.
  • Working knowledge of information and data retrieval.

ABOUT US

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

ABOUT THE TEAM

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.