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Data Annotation Manager Jobs in Lexington, SC (NOW HIRING)

Prolific

Data Quality Engineer, AI Business

North, SC

$106.30K - $127.70K/yr

What You'll Be Doing * Own end-to-end quality design for Prolific managed service studies ... What You'll Bring to the Role * 5+ years of experience in quality engineering, data or annotation ...

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Data Annotation Manager information

See Lexington, SC salary details

$26.5K

$83.2K

$147.2K

How much do data annotation manager jobs pay per year?

As of May 31, 2026, the average yearly pay for data annotation manager in Lexington, SC is $83,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,500.00 and $107,400.00 per year, depending on experience, location, and employer.

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 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.

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 Lexington, SC? The most popular types of Data Annotation jobs in Lexington, SC are:
What job categories do people searching Data Annotation Manager jobs in Lexington, SC look for? The top searched job categories for Data Annotation Manager jobs in Lexington, SC are:
What cities near Lexington, SC are hiring for Data Annotation Manager jobs? Cities near Lexington, SC with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you

Data Quality Engineer, AI Business

Prolific

North, SC

$106.30K - $127.70K/yr

Other

Posted 18 days ago

Job description

Data Quality Engineer, AI Business 

Team: Client Services

Prolific

Prolific isn't just enabling AI innovation - we're redefining it. While foundational AI technologies are becoming commoditized, Prolific's human data infrastructure provides the high-quality, diverse data required to train the next generation of AI models. Through our platform, we empower researchers and companies to access a global, ethically curated participant base, ensuring cutting-edge AI research and training grounded in inclusivity and precision.

The Role

As a Data Quality Engineer within Prolific AI Data Services, you will be the quality guardian for our managed service studies. You will design and operationalise the measurement systems, automation, and launch gates that ensure the data we deliver is trustworthy, authentic, and scalable.
This role sits at the intersection of data quality, automation, and integrity. You'll work closely with Product, Engineering, Operations, and Client teams to embed quality and authenticity into study design and execution-enabling faster launches without compromising trust as task types and volumes evolve.

What You'll Be Doing

  • Own end-to-end quality design for Prolific managed service studies, including rubrics, acceptance criteria, defect taxonomies, severity models, and clear definitions of done.
  • Define, implement, and maintain quality measurement systems, including sampling plans, golden sets, calibration protocols, agreement targets, adjudication workflows, and drift detection.
  • Build and deploy automated quality checks and launch gates using Python and SQL, such as schema and format validation, completeness checks, anomaly detection, consistency testing, and label distribution monitoring.
  • Design and run launch readiness processes, including pre-launch checks, pilot calibration, ramp criteria, full-launch thresholds, and pause/rollback mechanisms.
  • Partner with Product and Engineering to embed in-study quality controls and authenticity checks into workflows, tooling, and escalation paths.
  • Write and continuously improve guidelines and training materials to keep participants, reviewers, and internal teams aligned on evolving quality standards.
  • Investigate quality and integrity issues end to end, running root-cause analysis across guidelines, UX, screening, training, and operations, and driving corrective and preventive actions (CAPAs).
  • Build dashboards and operating cadences to track defect rates, rework, throughput versus quality trade-offs, integrity events, and SLA adherence.
  • Lead calibration sessions and coach QA leads and reviewers to improve decision consistency, rubric application, and overall quality judgement.
  • Translate one-off quality fixes into repeatable, scalable playbooks across customers, programs, and study types.

What You'll Bring to the Role

  • 5+ years of experience in quality engineering, data or annotation quality, analytics engineering, trust and integrity, or ML/LLM evaluation operations.
  • Strong proficiency in Python and SQL, with comfort applying statistical concepts such as sampling strategies, confidence levels, and agreement metrics.
  • A proven track record of turning ambiguous or messy quality problems into clear metrics, automated checks, and durable process improvements.
  • Strong quality systems thinking, with the ability to translate complex edge cases into clear rules, tests, rubrics, and governance mechanisms.
  • Hands-on experience instrumenting workflows and implementing pragmatic automation that catches quality and integrity issues early.
  • Demonstrated ability to influence cross-functional teams (Product, Engineering, Operations, Client teams) and drive change without direct authority.
  • Strong customer empathy, with a clear understanding of what "useful, trustworthy data" means for research, AI training, and evaluation use cases.
    Even Better if you have:
  • Familiarity with data collection mechanics (screeners, quota/routing constraints, study design patterns).
  • LLM evals, red teaming, or policy-based annotation experience.
  • Data/versioning discipline (dataset lineage, change control, reproducibility).
  • Experience with integrity/fraud detection systems and anti-abuse tooling

Why Prolific is a great place to work

We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioral data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.

We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviors into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation - one that reflects the breath and the best of humanity.

Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research.

Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture. At Prolific, our compensation packages for eligible roles include base salary, equity, and benefits. Many roles also include the opportunity to earn a cash variable element, such as a bonus or commission. Each job posting shows a salary range that reflects the minimum and maximum target for new hires, based on the role's location as well as your skills, experience, and relevant education or training. Your recruiter will also be happy to share the specific salary range for your preferred location during the hiring process.

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By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.

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