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Accenture - Data Scientist - Merchandising / Retail Domain

Accenture - Data Scientist - Merchandising / Retail Domain

Accenture OperationBangalore
11 days ago
Job description

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)

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