Job description

The Senior Data Scientist II – Supply Chain role at Careem is part of a technology-driven organisation building an Everything App across the Middle East, operating in over 70 cities across 10 countries. The company enables mobility, food and grocery delivery, payments, and logistics services and is now entering an AI-powered transformation phase focused on automation, optimisation, and intelligent systems. The role focuses on architecting and scaling intelligent systems that act as the ‘brain’ of dark store operations, optimizing end-to-end supply chain lifecycle from supplier dispatch to last-mile delivery within ultra-fast delivery constraints of under 20 minutes. The Senior Data Scientist is responsible for building and deploying high-precision demand forecasting models at SKU-store level, developing replenishment and inventory optimization algorithms, and managing perishable trade-offs between stock availability and product expiry. The role includes designing machine learning systems to reduce wastage through predictive expiry risk modelling and automated interventions such as discounting and intra-store replenishment. The position involves dynamic pricing and discount optimization using experimentation and A/B testing to improve inventory flow and margin performance. The Senior Data Scientist also optimizes dark store spatial layout to reduce picker travel time and maximize storage density. The role requires end-to-end ownership of models, working closely with Product Managers and Supply Chain Operations to deploy production-grade machine learning systems that directly influence real-world logistics operations. The position demands expertise in Python, Spark, ML frameworks, optimization libraries, and advanced techniques such as stochastic optimization and reinforcement learning. The role also requires strong experimentation skills, causal inference knowledge, and experience with real-time inference systems and model monitoring in production environments. The candidate is expected to translate complex analytical models into measurable business impact, including EBITDA optimization through supply chain efficiency improvements.