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Full Time Data Annotation Tech Jobs in Spartanburg, SC

GSP International Airport

Data Strategist

Greer, SC · On-site

$81K - $101K/yr

Salary Level 10 Full-Time Exempt Typical Hiring Range: $81,563 - $101,954 Position Summary (Primary ... Education Requirements • Bachelor's degree in Information Technology, Computer Science, or a ...

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Full Time Data Annotation Tech information

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$11

$22

$34

How much do full time data annotation tech jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for full time data annotation tech in Spartanburg, SC is $22.32, according to ZipRecruiter salary data. Most workers in this role earn between $16.44 and $26.54 per hour, depending on experience, location, and employer.

What is a full time data annotation tech?

Full Time Data Annotation Techs are professionals responsible for labeling and categorizing data used to train machine learning models. They examine various types of data, such as images, text, or audio, and apply specific tags or annotations according to project guidelines. Their work is essential in ensuring the accuracy of artificial intelligence systems by providing high-quality, structured datasets. Full-time positions typically involve working standard business hours and may require familiarity with specialized annotation tools and attention to detail.

What are the key skills and qualifications needed to thrive as a full time data annotation tech?

To thrive as a Full Time Data Annotation Tech, you need strong attention to detail, basic data management skills, and familiarity with data labeling practices, typically supported by a high school diploma or equivalent. Experience with annotation tools (such as Labelbox, Supervisely, or similar platforms) and basic proficiency in spreadsheet or database systems are commonly required. Reliability, consistency, and effective communication are crucial soft skills for quality assurance and collaboration with data teams. These skills and qualities are essential to ensure the accuracy and efficiency of annotated datasets, which directly impact the performance of machine learning models.

How does a full time data annotation tech typically collaborate with data scientists and engineers on projects?

As a Full Time Data Annotation Tech, you will regularly work alongside data scientists and engineers to ensure the accuracy and quality of labeled datasets used for machine learning models. Collaboration often involves attending project meetings to clarify annotation guidelines, providing feedback on ambiguous data cases, and updating annotation processes based on team input. Clear communication is essential, as your work directly impacts model performance and downstream analytics. This team-oriented environment fosters learning and provides insight into broader AI development workflows.

What is the difference between Full Time Data Annotation Tech vs Data Labeling Specialist?

AspectFull Time Data Annotation TechData Labeling Specialist
CredentialsBasic computer skills, attention to detailSimilar credentials, often with training in labeling tools
Work EnvironmentOffice or remote, collaborative teamsRemote or on-site, focused on labeling tasks
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, healthcare
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI accuracy

Both roles involve data annotation and labeling, often requiring similar skills and working environments. The main difference lies in job titles used by employers and the scope of responsibilities, with 'Full Time Data Annotation Tech' emphasizing a broader technical role, while 'Data Labeling Specialist' may focus more on specific labeling tasks.

Does full time data annotation tech actually pay?

Full-time data annotation technicians typically receive a regular salary or hourly wage, with pay rates varying based on experience, location, and company. Many roles offer benefits such as paid time off and health insurance, and some positions may require familiarity with annotation tools or specific data types.

What are popular job titles related to Full Time Data Annotation Tech jobs in Spartanburg, SC?

For Full Time Data Annotation Tech jobs in Spartanburg, SC, the most frequently searched job titles are:

What job categories do people searching Full Time Data Annotation Tech jobs in Spartanburg, SC look for?

The top searched job categories for Full Time Data Annotation Tech jobs in Spartanburg, SC are:

Full Time Data Annotation Tech jobs near you
Infographic showing various Full Time Data Annotation Tech job openings in Spartanburg, SC as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $46,421 per year, or $22.3 per hour.

Fraud Data & Technology Analyst

United Community Bank

Greenville, SC

$56K - $74K/yr

Full-time

Posted 29 days ago

Job description

Overview

The Fraud Data & Technology Analyst drives data-informed decision-making through analytics, reporting, technology support, and rule optimization. This role delivers actionable insights, evaluates fraud trends and program performance, and supports initiatives that strengthen detection, prevention, and mitigation capabilities. Working closely with the Fraud Data & Technology Lead and cross-functional partners, the analyst helps optimize fraud technologies, enhance controls, improve operational effectiveness, and strengthen customer protection.

This position is available in Greenville, SC and Blairsville, GA. 

What You'll Do
  • Reporting & Analytics
    • Build, automate, and maintain fraud KPIs, dashboards, and reports to measure program performance, loss drivers, mitigation outcomes, and emerging fraud trends.
    • Analyze fraud data and translate complex findings into actionable insights, recommendations, and strategic reporting for leadership, operations, and frontline teams.
    • Conduct performance assessments, cost-benefit analyses, business case development, and industry research to support fraud strategy, risk identification, and continuous improvement initiatives.
  • Fraud Technology Support
    • Support the administration, maintenance, optimization, and performance of fraud-related applications, platforms, tools, and system enhancements.
    • Coordinate and participate in testing, validation, implementation, troubleshooting, issue resolution, and performance monitoring to ensure technology effectiveness and operational reliability.
    • Partner with internal technology teams, business stakeholders, and vendors to support fraud technology initiatives while documenting business processes, system functionality, and operational workflows for governance and knowledge sharing. 
  • Rules & Model Management
    • Tune, calibrate, and optimize fraud detection rules, models, and decisioning strategies to improve detection effectiveness while balancing operational efficiency and customer experience.
    • Analyze rule and model performance through testing, alert reviews, and performance metrics, recommending enhancements to fraud monitoring strategies and detection controls.
  • Data Management
  • Ensure the accuracy, integrity, reliability, and quality of data used in fraud reporting, analysis, and decision-making.
  • Support data governance initiatives through documentation, maintenance of data dictionaries and reporting methodologies, quality validation, issue identification, and adherence to reporting standards. 
  • Cross-Functional Partnership
    • Collaborate with stakeholders to identify opportunities for process improvements, automation, and enhanced fraud controls.
    • Partner with Fraud Operations, Risk, Compliance, IT, and business teams to support fraud mitigation efforts.
    • Provide analytical support and subject matter expertise for fraud-related initiatives.
Requirements For Success
  • Bachelor's degree or higher preferred
  • 3+ years of experience in fraud analytics, fraud technology or operations, risk management, or a related field.
  • Required Skills:
    • Hands-on experience with fraud and/or banking platforms.
    • Experience with data visualization and reporting tools (e.g., Tableau, Power BI, etc.).
    • Experience querying and analyzing large datasets using SQL or similar data analysis tools.
    • Knowledge of fraud typologies across payments, digital identity, account takeover, and application fraud.
    • Strong analytical, problem-solving, and communication skills.
    • Demonstrated ability to collaborate effectively with cross-functional teams. 
  • Preferred Skills:
    • Experience with machine learning concepts or partnering with data science teams.
    • Experience creating or maintaining process maps for technical or operational processes
    • Familiarity with APIs, system integrations, or cloud-based data environments.
    • Ability to present complex data insights in a clear and concise manner to both technical and non-technical audiences.
Conditions of Employment
  • Must be able to pass a criminal background & credit check
  • This is a full-time, non-remote position that requires schedule flexibility to work evenings and weekends as needed.
  • Up to 10% of travel may be required.

FLSA Status: Exempt

Ready to take your career to the next level? Apply now and become a vital part of our team!

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state, or local protected class.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Pay RangeUSD $56,000.00 - USD $74,000.00 /Yr.Employment Type: FULL_TIME

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