Retail Merchandising Growth Lead

Role Title: AI Replenishment Intelligence Lead Location: Delhi, India | On-site | Full-time Mission Brief: Reinvent How Lenskart Never Runs Out — or Runs Over This is not a replenishment role. This is a product transformation mandate . Lenskart operates one of India's largest and fastest-scaling retail networks — thousands of stores, millions of SKUs, and a supply chain that must move at the speed of fashion and the precision of science. Today, our replenishment function is being fundamentally reimagined: from reactive and rule-based to predictive, intelligent, and productized as a scalable AI platform . You will be the architect of that shift. As the AI Replenishment Intelligence Lead , you will own the end-to-end product vision, design, and deployment of Lenskart's AI-driven replenishment platform — a system that ensures the right product reaches the right store at the right moment, every time. You will operate at the intersection of machine intelligence, product management, and retail operations , converting data into decision systems that directly drive availability, profitability, and customer delight across India and global markets. If you've been waiting for a role where AI is not a feature but the core product , this is it. 🔑 Core Mandate 1. AI Platform Development — Build the Brain Own the product vision, roadmap, and lifecycle of Lenskart's replenishment intelligence platform. Define and evolve the product architecture for real-time inventory visibility, ML-driven demand forecasting, dynamic safety stock models, and system-generated replenishment decisions that eliminate manual intervention. Translate complex retail and supply chain problems into clear product requirements, user stories, and technical specifications for Data Science and Engineering teams. [REDACTED]/ML capabilities within replenishment, ensuring models are production-ready, scalable, and continuously improving. Drive success through clearly defined product metrics such as forecast accuracy (MAPE/WAPE), fill rates, inventory turns, and system adoption — and own these as core product KPIs. 2. Intelligent Assortment & Inventory Optimization — Drive the Business Build and scale AI-powered product features that solve high-impact commercial problems: assortment optimization (store-wise product mix), demand sensing across fashion cycles, and automated markdown and liquidation intelligence. Design systems that dynamically connect inventory decisions with financial and customer outcomes , influencing working capital efficiency, sell-through, and availability. Transform Open-to-Buy into a real-time, system-led product capability , where buying signals are continuously optimized based on live demand, inventory health, and business goals — moving from static planning to always-on decisioning systems . 3. Cross-Functional Leadership — Drive Adoption Drive product adoption and behavioral change across Merchandising, Supply Chain, Finance, and Retail Operations. Ensure the platform is not just built, but deeply embedded into daily decision-making. Act as the voice of the user , continuously refining the product based on stakeholder feedback, usability insights, and operational realities. Build, mentor, and elevate a team of planners and analysts to operate as product users and contributors , fostering a culture of experimentation, data fluency, and trust in AI-led systems. The Essentials Experience: 5–8 years in product management, inventory planning, supply chain product roles, or merchandise planning , with demonstrable experience building or owning AI/ML-driven products or decision systems — not just using them. Technical Depth: Hands-on familiarity with demand forecasting methodologies (time-series models, statistical and machine learning approaches), replenishment algorithm design, and the ability to translate these into scalable product features and system requirements . Education: Degree in AI/ML, Data Science, Operations Research, Engineering, or a highly quantitative field. Top-tier MBA a strong plus. Domain Knowledge: Strong understanding of retail operations, SKU-level planning, supply chain dynamics, and how fashion cycles complicate inventory logic — with the ability to translate these into product constructs and decision frameworks . The Mindset AI-Native Thinking: You don’t add AI to products — you build products around AI capabilities . You understand model strengths and limitations and design systems accordingly. Builder’s Instinct: You treat replenishment as a living product — iterating rapidly, measuring impact, and continuously improving. Analytical Rigor at Speed: You move from ambiguity to clarity fast — translating complex signals into scalable product decisions and features . Transformational Leadership: You drive alignment, build trust in AI systems, and lead product adoption across diverse stakeholders , turning skepticism into advocacy. Equal Opportunity Statement At Lenskart, we are committed to building a diverse, inclusive, and equitable workplace. We welcome applicants from all backgrounds, experiences, and identities — because the best intelligence, human or artificial, comes from many perspectives