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

I have been with Accenture for more than five years and I like the diversified role that I play. By offering diversified roles, which gave me the opportunity to learn different processes other than my forte is the way Accenture groomed me into becoming a leader. I believe being a woman in this industry, one can contribute in creating a positive work environment and my one advice to all women consi...