Retail Merchandising AI Evaluation Specialist

You will create realistic retail planning exercises and evaluate how well AI-generated or submitted solutions handle practical merchandising decisions. The work combines retail judgment, commercial modeling, structured scoring, and clear written explanations.

You will also help set consistent evaluation standards by reviewing work with peers, using calibration feedback, and resolving difficult cases involving retail math and allocation logic.

• Design exercises covering assortment planning, promotional strategy, product allocation, planograms, and retail commercial modeling.
• Create gold-standard solutions that show sound merchandising methods.
• Score retail planning submissions against structured evaluation rubrics.
• Build and assess scenarios using sell-through, GMROI, open-to-buy, margin mix, and inventory turnover metrics.
• Review peer work, incorporate calibration feedback, and resolve edge cases involving allocation logic and retail math.

This is a contractor engagement lasting 12 weeks. The role is open worldwide and requires professional fluency in English.

The work calls for hands-on retail merchandising or related commercial planning experience, along with the ability to explain decisions clearly and apply structured evaluation standards.

• Pay: The listing does not specify a rate.
• Commitment: 20 or more hours per week, with at least four hours per day and up to 40 hours per week.
• Schedule requirement: Four hours of overlap with Pacific Time.
• Experience: 3 to 15 years in retail merchandising, buying, category management, or inventory allocation.
• Expertise in assortment architecture, product allocation, and merchandise financial planning.
• Experience creating and analyzing assortment plans, visual planograms, and promotional calendars.
• Strong command of GMROI, inventory turns, markdowns, margin impact, and weeks of supply.
• Ability to work through peer review, follow structured rubrics, and communicate decisions in writing.
• A bachelor's degree or equivalent practical experience.
• Background in AI evaluation, data annotation, content review, quality assurance, or related analytical work is helpful.

Apply on OpenTrain with your resume, then complete the application on the hiring site. OpenTrain is where people find AI training and data-labeling work, build a profile, and start applications.

AI training is the human work behind artificial intelligence. People create examples, review model outputs, and score results so AI systems can improve. Experienced professionals are needed when a project requires sound judgment in a specialized field such as retail merchandising.