Job Title : Data Scientist - Merchandising
Level : 9-Consultant
Relevant experience : 3 - 4 years
Role Overview : Mandate :
We are seeking a highly skilled Merchandising Data Scientist with deep expertise in retail merchandising strategies (pricing, promotions, assortment, category management) and proven experience delivering production-grade AI solutions.
The ideal candidate has successfully driven multiple production deployments of merchandising strategies in retail environments and is now ready to leverage Generative AI, agent-based architecture, and Retrieval-Augmented Generation (RAG) to reimagine decision support for merchants and category managers.
This role requires a balance of technical depth, retail domain knowledge, and innovation mindset-with the ability to design, build, and scale solutions that deliver measurable business impact.
Key Responsibilities :
- Merchandising Strategy AI : Design and deploy AI / ML models for pricing optimization, promotion planning, markdowns, and assortment management.
- Production Deployments : Lead and manage end-to-end lifecycle of merchandising solutions, from POC - MVP - scaled deployment, ensuring measurable business outcomes.
- Generative AI & Agents :
1. Build GenAI-powered assistants for merchants and category managers.
2. Architect agent workflows with RAG, ensuring responses are grounded in trusted retail data.
3. Apply Multi-Component Protocol (MCP) to orchestrate agent interactions with merchandising systems.
Data Science & Engineering : Develop predictive models, demand forecasts, and optimization algorithms using advanced ML techniques.Innovation & POCs : Partner with category managers and business teams to design new proofs-of-concept, drive innovation, and scale successful experiments into enterprise-ready products.Cross-Functional Collaboration : Work closely with product managers, engineers, data engineers, and business stakeholders to align technical solutions with merchandising goals.Domain Expertise : Bring thought leadership in retail merchandising trends, competitor analysis, and applying AI for better business decisions.Scalability & Governance : Ensure solutions comply with data governance, ethics, and responsible AI guidelines while maintaining scalability and performance.Qualifications & Skills :
Technical Skills :
Strong background in data science, applied ML, and optimization techniques.Hands-on expertise with Generative AI (LLMs, RAG, Vector DBs, LangChain / Semantic Kernel).Experience with agent frameworks and orchestration protocols (e.g., MCP).Proficiency in Python, SQL, PySpark; experience with cloud platforms (Azure, GCP, AWS).Deployment experience using CI / CD pipelines, MLOps frameworks (MLflow, Kubeflow, Databricks).Retail & Merchandising Skills :
Deep domain knowledge of pricing, promotions, assortment, category management, and demand forecasting.Proven success delivering production-grade merchandising AI solutions that drove measurable KPIs (margin lift, sales uplift, markdown optimization).Strong understanding of retail datasets : POS, transaction logs, promotion history, competitive pricing data, loyalty / customer data.Innovation & Leadership :
Experience leading POCs and pilots, scaling them to enterprise deployments.Ability to translate business needs of category managers into technical AI solutions.Strong communication skills; able to influence and partner with senior retail stakeholders.Prior contributions to research, patents, or innovation programs in retail AI are a plus.Preferred Background :
3+ years in data science / applied ML, with at least 3+ years in retail merchandising strategy.Experience working with retailers, CPG companies, or consulting firms in the merchandising / assortment domain.Exposure to GenAI use cases in retail such as smart assistants, intelligent search, automated negotiation, or category insights.Strong track record of delivering measurable value through AI-driven merchandising strategies(ref : hirist.tech)