E-commerce Data & Catalog Specialist — Remote Contract

About OpenTrain

OpenTrain is the centralized platform where people find and grow careers in AI training and data labeling. We help contributors discover projects, build a unified AI training portfolio, and apply quickly so they can build durable freelance careers in a fast-growing industry.

Working through OpenTrain connects you to structured, real-world AI training projects—where your work directly shapes how models learn and behave.

Why this work matters

AI models learn from examples prepared by people. E-commerce catalogs and structured product data are core training inputs for shopping, recommendation, and search systems. Accurate catalogs, thoughtful taxonomies, and realistic shopping scenarios help models understand how consumers discover and choose products.

This role offers flexible, remote contract work that lets you apply catalog management skills to shape how AI systems handle product information at scale.

The role

OpenTrain is recruiting an E-commerce Data & Catalog Specialist to support AI training work built around large-scale product catalogs and structured e-commerce data. This is a part-time contract role (20+ hours/week) paid hourly at $40–$50 USD and open to remote contributors worldwide.

You will work closely with AI development teams to prepare, normalize, and document product datasets used for evaluation, rating, and data-collection tasks.

• Employment type: Contractor, Part-time
• Hours: 20+ hours/week (flexible)
• Pay: $40–$50 USD per hour
• Work type: Remote, worldwide (English required)

What you'll do

Day-to-day responsibilities center on structuring, curating, and validating large product catalogs so they can be used effectively in AI training pipelines.

• Manage, structure, and curate large-scale e-commerce product catalogs with a focus on accuracy and consistency.
• Develop and refine product taxonomy frameworks that reflect real-world browsing and classification behavior.
• Normalize product data from diverse sources and support structured dataset management across SQL and NoSQL environments.
• Create realistic shopping scenarios that model authentic consumer decision-making for evaluation tasks.
• Collaborate with AI teams to define data needs and optimize catalog structures for scalable model training.
• Document workflows, taxonomies, metadata, and schema decisions clearly and concisely.

Requirements

To succeed in this role you should bring hands-on catalog skills, technical knowledge of structured data, and strong written communication for documentation.

• Product catalog management and e-commerce merchandising operations experience.
• Knowledge of SQL and NoSQL database concepts, schema design, and product data modeling.
• Experience with product taxonomy development, categorization, and data normalization methods.
• Experience managing structured datasets for large and complex e-commerce catalogs.
• Clear written and verbal communication for documenting processes and technical concepts.
• Ability to build data-driven shopping experiences and simulate consumer journeys.
• High attention to detail and experience working collaboratively across functions.

Preferred experience

These qualifications are not required but will help you hit the ground running and increase impact on AI training outcomes.

• Previous involvement with AI, machine learning, or data annotation projects.
• Experience designing scalable catalog schemas for online marketplaces.
• Background with advanced metadata structures or prior AI training initiatives.

Project details and labeling work

This role involves document-style data work: reviewing and preparing product records, creating evaluation/rating tasks, and supporting data collection efforts. You will use unspecified (OTHER) annotation tooling and follow strict data quality and normalization standards.

• Data type: Document (product records, metadata, taxonomies).
• Labeling tasks: Evaluation/rating and data collection for catalog quality and behavior simulation.

How to apply and next steps

If this role matches your skills and availability, apply through OpenTrain with your resume and examples of catalog or schema work (samples, repo links, or documentation). Include a short note describing a complex taxonomy or normalization challenge you solved.

Selected candidates will complete a technical screening and short task to demonstrate catalog modeling and documentation ability before onboarding.

• Language: English required.
• Time commitment: 20+ hours/week, flexible scheduling.
• Compensation: Hourly, $40–$50 USD per hour.