Data Science Manager, Courier Pay

We’re a leading global online delivery platform, and our vision is to empower everyday convenience. Whether it’s a Friday-night feast, a post-gym poke bowl, or grabbing some groceries, our tech platform connects tens of millions of customers with hundreds of thousands of restaurant, grocery and convenience partners across the globe. Logistics is the engine room of that platform. Every order depends on a web of real-time decisions - matching couriers to deliveries, predicting arrival times, balancing supply and demand, and pricing a marketplace that never stops moving. Data science sits at the heart of these decisions, and the quality of our models directly shapes courier earnings, customer experience, and the unit economics of the business. As Data Science Manager for Logistics, you'll lead a team building robust, well-engineered, data-driven solutions to exactly these problems. You'll own the vision and execution of data science for your vertical - setting the strategy, raising the technical bar, and developing a team of senior scientists and team leads - while staying close enough to the work to guide hard modelling decisions. Your remit is both deep and broad: translate the toughest logistics challenges into modelling strategies, then hold the team accountable for solutions that move the metrics that matter. This is a high-impact, high-ownership role for someone who wants their team's work to be felt across a global operation every single day. Lead, coach, and scale a high-performing team of up to 20 Data Scientists, Operations Research Scientists, and Machine Learning Engineers. Build a durable leadership bench by mentoring senior individual contributors and team leads toward management and staff-level impact. Strategic owner of hiring, workforce planning, and organizational design to structure the team effectively as it scales. Own the logistics data science roadmap, partnering with cross-functional leadership to identify and prioritize high-leverage business opportunities. Translate intricate logistics challenges like network congestion, pricing inefficiencies, and supply shortfalls into robust modeling strategies. Represent the vertical on the data leadership team, driving tooling and operational standards that elevate data science across the entire company. Collaborate with ML Engineering to architect, deploy, and monitor highly scalable, production-ready machine learning systems. Act as the primary data science voice to VP-level stakeholders, translating complex model behavior into business outcomes that move key logistics metrics. Data Science, Statistics, Operational Research, Mathematics, Computer Science, or similar. A proven track record leading high-performing data science teams in a fast-moving product or tech environment, with direct management experience across senior ICs and team leads. Deep expertise in machine learning, optimisation, and statistical modelling, with strong intuition for where these techniques create real business leverage. Hands-on experience building and deploying ML models in production, ideally in real-time or high-throughput systems. Strong commercial instincts, connecting modelling decisions to P&L, courier supply health, and customer experience. Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment. It's a competition for something incredibly valuable – our customers' choice.