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Entry Level Data Annotation Tech Jobs (NOW HIRING)

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

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Entry Level Data Annotation Tech information

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$26

How much do entry level data annotation tech jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for entry level data annotation tech in the United States is $19.34, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.39 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Data Annotation Tech vs Entry Level Data Labeler?

AspectEntry Level Data Annotation TechEntry Level Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech-focusedRemote or on-site, tech-focused
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, autonomous vehicles

Both roles involve labeling data for AI training, requiring similar skills and environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes the technical aspect of annotation, while 'Data Labeler' is a more general term. Both are entry-level positions vital for AI development in tech industries.

What are some common challenges faced by Entry Level Data Annotation Techs, and how can they be managed?

Entry Level Data Annotation Techs often encounter challenges like maintaining focus during repetitive tasks, ensuring accuracy under tight deadlines, and adapting to evolving annotation guidelines. To manage these, it's helpful to take regular breaks, double-check your work, and actively seek feedback from supervisors. Collaborating with teammates and participating in training sessions can also improve both speed and consistency, making the work more manageable and rewarding.

Can I use ChatGPT for data annotation?

Entry Level Data Annotation Technicians can use ChatGPT to assist with labeling and categorizing data, especially for text-based tasks. However, human oversight is essential to ensure accuracy and consistency, as AI tools may not fully understand context or nuances in complex data annotation projects.

What is an Entry Level Data Annotation Tech?

An Entry Level Data Annotation Tech is responsible for labeling and categorizing data, such as images, text, or audio, to help train machine learning models. This role typically involves using specialized software to accurately tag and classify data according to specific guidelines. It is a foundational position within the field of artificial intelligence and data science, requiring attention to detail and consistency. No advanced technical skills are usually required, making it a suitable entry point for those interested in AI or data-related careers.

Is it easy to get hired for data annotation?

Entry level data annotation jobs are generally accessible to beginners, as they often require minimal prior experience and focus on basic labeling skills. Employers typically look for attention to detail and the ability to follow instructions, and training is usually provided. Competition can vary depending on the platform and demand, but overall, these roles tend to have relatively straightforward hiring processes.

Can I do data annotation with no experience?

Entry level data annotation jobs typically do not require prior experience, as training is often provided to teach specific tools and guidelines. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Developing familiarity with annotation tools and understanding data labeling standards can improve job performance and opportunities for advancement.

How to get into data annotation tech?

To get into data annotation tech, candidates typically need basic computer skills and attention to detail. Many entry-level roles require no formal degree, but familiarity with tools like labeling platforms and understanding data types can be helpful. Gaining experience through online tutorials or certifications in data labeling can improve job prospects.

What are the key skills and qualifications needed to thrive as an Entry Level Data Annotation Tech, and why are they important?

To thrive as an Entry Level Data Annotation Tech, you need strong attention to detail, basic computer literacy, and a high school diploma or equivalent. Familiarity with annotation software, data labeling platforms, and basic spreadsheet tools is typically required. Patience, consistency, and effective communication help ensure accuracy and efficient teamwork. These skills and qualities are essential for delivering high-quality labeled data that supports machine learning and AI development.
More about Entry Level Data Annotation Tech jobs
What cities are hiring for Entry Level Data Annotation Tech jobs? Cities with the most Entry Level Data Annotation Tech job openings:
What are the most commonly searched types of Data Annotation Tech jobs? The most popular types of Data Annotation Tech jobs are:
What states have the most Entry Level Data Annotation Tech jobs? States with the most job openings for Entry Level Data Annotation Tech jobs include:
Infographic showing various Entry Level Data Annotation Tech job openings in the United States as of June 2026, with employment types broken down into 80% Full Time, 12% Part Time, and 8% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $40,220 per year, or $19.3 per hour.
Data Domain Architect Lead

Data Domain Architect Lead

JP Morgan Chase

Wilmington, DE

Full-time

Medical, Retirement

Posted 16 days ago


JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 470 frontline employees who took The Breakroom Quiz

46th of 141 rated banks


Job description

Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop solutions which both our customers and employees can benefit from. Customers expect tailored servicing and Chase is looking to deliver personalization to meet their needs. This is powered by high-quality annotated data and detailed annotation schemes that are the backbone of impactful  Artificial Intelligence/Machine Learning ( AI/ML)L algorithms and applications.

As a Data Domain Architect Lead within the Data  Annotation team , you will use your domain expertise and people-leading experience to partner your team closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other linguistic resources to help train machine learning models, drive insight, analysis, and possible content creation.

Job responsibilities

  • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis

  • Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
  • Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
  • Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
  • Actively contribute to the team's continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group

Required qualifications, capabilities, and skills

  • 6+ years of related experience in development of machine learning solutions
  • Familiar with industry annotation and labeling methods
  • Experience with various data modeling techniques and tools
  • Familiar with Finance and Banking products
  • Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience using Python in working with and analyzing large real-world datasets
  • Working knowledge of information and data retrieval
  • Working knowledge of machine learning and artificial intelligence paradigms and libraries
  • Familiar with  Large Language Models (LLMs) and prompt engineering

Preferred qualifications, capabilities, and skills

  • Masters or PhD in a related field, or Bachelors 
  • Technical understanding of common relational database systems; i.e., Teradata and Oracle
  • Excellent command of the Structured Query Language (SQL)
  • Knowledge of SAS or Scala, and Python languages
  • Knowledge of Advanced Statistics
  • Advanced analytical thinking and problem-solving skills
  • Strong interpersonal & communication skills

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

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.

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