Merchandising Analytics

About The Role

• Strategic Advisory
• Act as a trusted advisor to clients by translating merchandising and category challenges into data-driven strategies.
• Lead client discovery workshops, assess current-state analytics maturity, and develop transformation roadmaps.
• Advise retailers on AI/ML use cases for pricing, assortment, inventory, and promotion optimization.
• Share thought leadership via industry forums, whitepapers, and client presentations.
• Business Development
• Support the sales team in qualifying leads, understanding client pain points, and positioning analytics solutions effectively.
• Own the solution design during RFP/RFI responses and client proposals.
• Build strong client relationships, influence buying decisions, and drive revenue growth in merchandising analytics offerings.
• Develop business cases and ROI models to help clients quantify the value of proposed solutions.
• Product Management
• Liaise between clients and product teams to align product capabilities with market needs.
• Provide inputs into product roadmaps, based on emerging trends and customer feedback.
• Conceptualize new analytics modules (e.g., markdown simulator, OTB optimizer) tailored to merchandising use cases.
• Create user stories and functional requirements for enhancements and demo assets.
• Solutioning Expertise
• Design end-to-end analytics solutions for merchandising use cases: assortment optimization, price elasticity, inventory planning, etc.
• Build and present proof-of-concepts, demos, and visualizations using tools like Power BI/Tableau.
• Collaborate with data science and engineering teams to validate feasibility and scalability of proposed solutions.
• Ensure seamless handover to delivery teams with clear documentation and expectations.
  

Required Qualifications

• Experience: 10+ years in the retail domain, with at least 3–5 years focused on merchandising (buying, planning, category management, etc.).
• Strong domain expertise across retail KPIs, merchandising workflows, and the impact of analytics on product, price, promotion, and placement.
• Demonstrated success in a pre-sales, consulting, or solution architect role for retail clients.
• Proficient in storytelling and stakeholder engagement, with the ability to communicate complex analytics solutions to non-technical audiences.
• Experience working with global retailers or in an omnichannel retail environment is highly desirable.