Role Overview
The Instock Analyst will be part of the MNow (Dark Store / Quick Commerce) Planning team, responsible for ensuring optimal stock availability across dark stores. This role blends inventory analytics, demand-side judgement, and hyperlocal planning to minimize stockouts and overstocks while supporting adherence to the DS (Data Science) replenishment model.
Key Responsibilities
- Monitor and analyze dark-store inventory health across cities using availability, sell-through, and sales-plan-vs-actual metrics to flag misallocation and stockout/overstock risk.
- Identify inventory redistribution opportunities within and across dark stores/cities to improve fill rate and reduce lost sales.
- Track adherence to the DS (Data Science) replenishment model and work with cross-functional stakeholders (Data Science, Category, Supply Chain) to resolve dependencies affecting model output — including sales plan inputs, store design alignment, FDC replenishment, RGM optimization, dark store RSTN, sourcing, and Mnow replenishment via Vulcan movement.
- Build and maintain local/hyperlocal demand signals to inform stock placement decisions at the store level, accounting for city- and store-specific demand patterns.
- Develop and refine availability planning processes to proactively identify and close instock gaps ahead of demand spikes (events, weekends, seasonal shifts).
- Perform advanced data analysis on inventory, sales, and demand datasets to generate actionable insights and recommendations for planning and category teams.
- Prepare regular reporting and dashboards summarizing instock performance, root causes of gaps, and progress on resolution.
- Present findings and recommendations to senior stakeholders in a clear, solutions-oriented manner.
Qualifications
- Bachelor's degree in Engineering, Statistics, Business Analytics, Supply Chain, or related field.
- Prior experience in inventory planning, retail analytics, or quick-commerce/dark-store operations preferred.
- Strong proficiency in Excel/SQL; familiarity with BI tools (e.g., Tableau, Power BI) a plus.
- Comfort working with large datasets and translating analysis into operational recommendations.
- Ability to collaborate across functions (Data Science, Category, Supply Chain, Store Ops) and communicate clearly with senior stakeholders.
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