Retail Domain Expert (Subject Matter Expert)

Work Location: US – Remote
Engagement Model: Freelancer / Independent Contractor
Start Date: ASAP

Qualification Requirements:

• Successful completion of a role-specific written assessment

• Successful completion of a background check

About the Role

DataForce by TransPerfect is seeking experienced Retail Subject Matter Experts (SMEs) to support a next-generation Generative AI and advanced analytics initiative. In this role, you will bring deep, hands-on retail expertise to help train, evaluate, and refine AI models that support intelligent retail solutions across operations, merchandising, supply chain, and customer experience.

You will work closely with data scientists, AI engineers, and product teams to ensure AI systems demonstrate strong contextual understanding, accuracy, and alignment with real-world retail workflows. This role is ideal for retail professionals who enjoy problem-solving, creative thinking, and applying their industry knowledge to emerging AI technologies.

Key Responsibilities

Domain Training & Data Annotation

• Serve as the retail domain expert during AI model training and fine-tuning, ensuring outputs reflect real-world retail practices and terminology.

• Annotate, label, and validate datasets using retail-specific knowledge, including:

• Product hierarchies and categories

• Inventory and replenishment terminology

• Pricing, promotions, and markdown strategies

• Store operations and customer experience data

• Develop and refine structured datasets that accurately represent retail business processes.

Workflow Definition & Knowledge Modeling

• Translate core retail workflows into structured, AI-ready representations.

• Define and document key retail workflows such as:

• Merchandising and assortment planning

• Inventory management and replenishment

• Demand forecasting and sales planning

• Store operations and labor optimization

• Omnichannel and e-commerce fulfillment

• Customer experience and loyalty management

• Develop knowledge bases, taxonomies, and ontologies aligned with retail industry standards and best practices.

Model Evaluation & Capability Assessment

• Design evaluation criteria and test cases to assess AI performance across retail use cases.

• Review AI-generated outputs for accuracy, relevance, and business applicability.

• Identify errors, ambiguities, and gaps in model reasoning and provide actionable feedback for improvement.

• Support prompt engineering and evaluation strategies tailored to retail applications such as virtual assistants, demand forecasting tools, and customer insight engines.

Cross-Functional Collaboration & Innovation

• Collaborate with AI/ML engineers to shape training data strategies, evaluation metrics, and model optimization approaches.

• Partner with product, analytics, and business teams to align AI capabilities with retail objectives, including:

• Increasing sales and conversion

• Improving demand forecasting accuracy

• Enhancing customer engagement and personalization

• Optimizing inventory and supply chain efficiency

• Stay current with emerging trends in retail technology, data platforms, and AI applications, contributing ideas for practical implementation.