Marketing Data Quality Control Reviewer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. Contributors use the platform to discover projects, consolidate opportunities, and build a unified AI training portfolio they control.

OpenTrain connects people to flexible, remote work that helps shape how modern AI systems behave — ideal for professionals who want part-time hours, varied projects, and an on-ramp into a fast-growing technical field.

About This Role

OpenTrain is recruiting for a Marketing Data Quality Control Reviewer to evaluate, rate, and label marketing-related text outputs used to benchmark and improve AI models. This is structured quality-control and annotation work guided by detailed rubrics.

The role is contract, part-time, with an immediate start preferred. Typical commitment is about 30 hours per week (minimum 20+ hours considered). Work is remote but limited to applicants living in the US, UK, or Canada and requires English fluency.

• Data type: Text
• Label types: Classification and evaluation/rating
• Employment: Contractor, Part-time
• Languages: English required
• Countries: US, GB, CA

What You'll Do

You will apply consistent judgment to large volumes of marketing text using clear evaluation rubrics. Tasks focus on quality control, annotation, and rating outputs so model teams can benchmark and iterate.

• Review and evaluate marketing-related text outputs for quality, accuracy, and relevance.
• Label and classify outputs according to detailed rubrics and examples.
• Assign evaluation ratings to support model benchmarking and improvement.
• Document edge cases and follow-up questions clearly for project leads.
• Maintain fast, consistent throughput while preserving high accuracy.

Requirements

All of the following are required for consideration. OpenTrain will expect demonstrable experience and the ability to follow detailed evaluation instructions precisely.

• 3–5 years of relevant marketing experience.
• Bachelor's degree or higher in Marketing, Business, Communications, or related field.
• MBA is required.
• Excellent written communication and research skills.
• Strong attention to detail and consistent judgment across repetitive tasks.
• Ability to understand and follow detailed evaluation rubrics and guidelines.

Who Should Apply

This role suits experienced marketing professionals who want flexible, remote work evaluating AI outputs. Ideal candidates enjoy structured review tasks, can maintain quality at scale, and want to contribute directly to how marketing-focused AI behaves.

• Marketing managers, strategists, or analysts with hands-on experience in campaign messaging, segmentation, or content evaluation.
• People who have used rubrics or QA processes in previous roles and can translate those skills to AI training.

Compensation and Schedule

This contractor role pays between $65 and $75 USD per hour. The project expects roughly 20–30+ hours weekly, with an immediate start preferred. Exact schedule and weekly hours will be coordinated with OpenTrain based on project needs.

• Pay type: Hourly (PAY_PER_HOUR), $65–$75/hr (USD).
• Time commitment: Approximately 30 hours/week typical; minimum 20+ hours considered.
• Contract status: Part-time contractor role; details agreed prior to start.

How It Works / Next Steps

To apply, create an OpenTrain account, complete your profile, and submit your application for this OpenTrain role. OpenTrain streamlines applications and helps you track work history and feedback across projects.

If selected, you will receive project onboarding materials, rubrics, and any required training. Work is performed in the labeling platform provided by the client or a third-party tool, and OpenTrain will supply evaluation guidelines and examples.

• Prepare a resume that highlights your marketing experience and MBA.
• Be ready to demonstrate attention to detail and to complete a short qualification test or sample task during onboarding.
• Questions about the project scope or schedule will be answered during the interview/onboarding conversation.