Associate - Instock Analyst

About The Company
Who are we?
Myntra is India’s leading fashion and lifestyle platform, where technology meets creativity. As pioneers in fashion e-commerce, we’ve always believed in disrupting the ordinary.
We thrive on a shared passion for fashion, a drive to innovate to lead, and an environment that empowers each one of us to pave our own way. We’re bold in our thinking, agile in our execution, and collaborative in spirit.
Here, we create MAGIC by inspiring vibrant and joyous self-expression and expanding fashion possibilities for India, while staying true to what we believe in.
We believe in taking bold bets and changing the fashion landscape of India. We are a company that is constantly evolving into newer and better forms and we look for people who are ready to evolve with us.
From our humble beginnings as a customization company in 2007 to being technology and fashion pioneers today, Myntra is going places and we want you to take part in this journey with us.
Working at Myntra is challenging but fun - we are a young and dynamic team, firm believers in meritocracy, believe in equal opportunity, encourage intellectual curiosity and empower our teams with the right tools, space, and opportunities.
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.
Skill
Inventory Management
Hyperlocal Stock Optimization
Availability Planning
Local Demand Prediction
Advanced Data Analysis
Python/SQL/Power BI/Google Scripts
Data Analytics and Insights
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.
Required Skills
inventory management, hyperlocal stock management, operational execution

Work arrangement
No