Product Manager - Inventory & Forecasting

About noon

noon is shaping a digital ecosystem powering everyday life in the Middle East with fast, scalable, and deeply customer-focused solutions. Its mission is to deliver to every door every day. Among its flagship offerings is Noon Minutes, the rapid hyper-local delivery service for FMCG and grocery products across UAE and Saudi Arabia, with delivery times as fast as 15 minutes.

Role Overview

As the Instock Product Manager for Noon Minutes, you will lead the end-to-end product strategy and implementation aimed at maximizing inventory availability. This role involves close collaboration with multifunctional teams including data science, engineering, operations, and commercial to maintain optimal product availability and minimize stockouts across all dark stores.

Key Responsibilities

• Drive the Instock product roadmap, prioritizing initiatives to enhance product availability and reduce out-of-stock rates.
• Collaborate with data scientists to design and refine demand forecasting models using machine learning, statistics, and operational insights, delivering accurate SKU-level predictions at hyper-local granularity.
• Develop replenishment algorithms and inventory optimization systems, translating mathematical models into scalable products.
• Define, monitor, and analyze instock metrics such as fill rate, out-of-stock percentage, waste percentage, and days of cover by leveraging Python and MySQL to excavate data insights.
• Engage hands-on with raw data through writing SQL queries, constructing dashboards, and validating model outputs without reliance on dedicated analysts.
• Partner with category management, supply chain, and operations teams to identify causes of stock discrepancies and translate findings into targeted product enhancements.
• Design and execute A/B testing and experiments on forecasting and replenishment strategies, rigorously assessing their effectiveness to drive improvements.
• Lead product discovery efforts involving interviews with warehouse managers, buyers, and operations leads to gather actionable product requirements.
• Specify APIs and data pipeline requirements for instock functions and collaborate closely with engineering to scope, design, and deploy robust backend systems.
• Promote a data-driven culture by applying quantitative analysis in every prioritization and product review process.

Required Qualifications and Skills

• Between 1 and 3 years of professional experience.
• Strong grounding in machine learning and statistical modeling, with understanding of forecasting algorithms including time-series analysis, regression, and gradient boosting.
• Proficiency in Python programming for production-level data analysis, model prototyping, and automation of data workflows.
• Advanced expertise in SQL/MySQL for complex query writing, analytical view creation, and handling sizable transactional datasets.
• Mathematical intuition with strengths in probability, optimization, and algorithmic problem solving to simplify complex operational challenges.
• Proven track record in delivering data-intensive product solutions from conceptualization through engineering design and deployment.
• Work experience in quick-commerce, e-grocery, FMCG, or dark store operations is an advantageous addition.
• Exceptional communication skills enabling translation of technical details to non-technical stakeholders and operational insights to engineering teams.
• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative discipline.

Desired Traits

• Commitment to high standards and recognition that diligent effort is key to success.
• Resourcefulness with a strong preference for taking initiative.
• Originality and courage in approach and thinking.
• Ability and willingness to adapt swiftly, pivot strategies, and continuously learn.