Market Research & Competitive Intelligence Evaluator
Evaluate AI-generated market research reports, spreadsheets, and slide decks for accuracy, rigor, and presentation quality—apply your competitive intelligence expertise to grade outputs and write structured feedback. Remote contract role, 20+ hrs/week, $80–$120/hr.
Generative AI & RLHF
100% Remote Hourly · $80–$120/hr
$80–$120/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jul 10, 2026
Posted
Open worldwide
Interested in this role?
Create a free OpenTrain account and apply in minutes.
OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help contributors find and grow work teaching AI: discover projects, build a unified training portfolio, and manage contracts in one place. Creating an OpenTrain account is free.
For this role, OpenTrain is the hiring organization and will contract directly with evaluators to perform review and feedback work on AI-generated market research materials.
Why AI training matters
AI training (also called data labeling or human feedback work) is the human side of building modern AI systems. Experts like you help models learn by grading outputs, identifying errors, and shaping how AI produces research and intelligence.
This work is often fully remote, flexible in schedule, and accessible to people with relevant domain knowledge. It’s a chance to work on cutting-edge systems while using your market research experience.
100% remote and flexible work that fits alongside other commitments
Direct impact on how AI systems produce and evaluate market research
Accessible entry points for experienced practitioners; specialist skills are highly valued
The role
You will evaluate AI-generated market research and competitive intelligence deliverables—documents, spreadsheets, and slide decks—against domain-specific rubrics. Your judgments and written feedback will help improve accuracy, analytical rigor, and presentation quality.
This is a remote, hourly contractor engagement. Projects move quickly and expect prompt turnarounds; tasks typically take 1 to 5 hours each, and the role requires a reliable 20+ hours per week commitment.
Position type: Contractor, part-time (hourly)
Typical task length: ~1–5 hours each
Time expectation: 20+ hours per week
What you'll do
Evaluate AI-generated market research and competitive intelligence outputs against provided quality rubrics
Review documents, spreadsheets, and slide decks for factual errors, methodological issues, and presentation problems
Write clear, structured feedback grounded in domain expertise to guide model and workflow improvements
Apply professional judgment to assess accuracy, rigor, completeness, and aesthetic quality
Requirements
5+ years of professional experience in market research or competitive intelligence
Experience evaluating AI-generated documents, spreadsheets, or slide decks
Demonstrated ability to identify factual, methodological, aesthetic, and presentation errors
Strong written-feedback skills and experience applying rubric-based judgments
Native or professional fluency in English
Proficiency with Microsoft Office and Google Workspace, especially Google Slides or PowerPoint
Advanced degree preferred (not required)
Compensation, schedule, and expectations
Pay is hourly at $80–$120 USD per hour. This is a fast-moving project with quick start expectations; prompt turnaround and careful adherence to task guidelines are essential.
You will be contracted and paid through OpenTrain. Tasks are distributed as they become available; maintain clear communication and timely delivery to succeed in this role.
How to apply and next steps
Create a free OpenTrain account, complete your profile, and apply to this posting. OpenTrain will manage onboarding, contracting, and task assignments for evaluators.
Successful applicants will complete a qualification or sample evaluation to confirm rubric understanding and feedback quality before receiving paid tasks.
Application step: sign up on OpenTrain and submit relevant experience
Qualification: complete a short sample evaluation to demonstrate rubric use and feedback clarity
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