Applied Science

Requirements

• Passion for Applied Science: You identify as a problem solver who loves leveraging data science, machine learning and AI to drive business results and create real-world impact.
• Expertise in Production-Ready ML Solutions: You know what it takes to build robust, scalable models suitable for large-scale deployments. You’re comfortable managing the entire lifecycle of data science projects, from ideation through to production and ongoing maintenance.
• Strong Foundations in ML and Statistics: You bring a solid educational background and practical skills in modeling and statistics, enabling you to design reliable and meaningful solutions. You know how to deal with time-series data and produce reliable forecasts at scale. We value experience with Bayesian methods and optimization.
• Engineering Excellence: You’re skilled in writing production-level Python code and following engineering best practices, ensuring your solutions are efficient, maintainable, and scalable. You have both read and written some SQL in your time and don’t find it scary. You have the ability (or willingness to learn) to productionalize ML solutions with our ML tooling.
• Clear Communication: You can effectively communicate complex technical concepts to non-technical audiences, bridging the gap between applied science and business needs.
• Analytical Problem-Solving: You excel at breaking down complex business challenges into clear, solvable machine learning problems, and designing data-driven solutions to address them. You understand that model metrics are most valuable when they are connected to business outcomes.
• Understanding of Experimental Design: You have a good grasp of experimental methodologies and analysis, allowing you to support experimentation and validation of the impact of your work.
• Experience in procurement and supply-chain optimization: We will value knowledge of procurement and inventory management processes, especially in fresh items and retail domains.

What you'll be doing

• We’re seeking an Applied Scientist to join our cross-functional Supply & Demand team. The team develops algorithms and tooling that balance courier supply with customer demand, helping ensure orders are delivered reliably and on time while making efficient use of our courier network.
• In close collaboration with software engineers, product managers, designers, and analysts, you’ll develop algorithms and data-driven products spanning demand and supply forecasting, causal inference, budget allocation, and optimization. You’ll apply machine learning, forecasting, optimization, and statistical modeling to solve large-scale operational challenges that directly improve delivery quality, courier experience, and marketplace efficiency.
• You’ll have a clear business impact by helping maintain the right balance between couriers and orders, reducing delivery times, improving reliability for customers, and enabling more efficient marketplace operations. In addition, you’ll develop insights and decision-support tools that empower our Operations teams to effectively manage delivery zones and optimize marketplace performance.

Perks and benefits

• This role gives you the chance to work on real, practical problems that directly impact how merchants manage their inventory every day. Your forecasting and optimization models won’t stay theoretical – they’ll be turned into tools used at scale, improving availability and efficiency across the platform.
• You’ll work closely with engineers, product managers and analysts, with real ownership from idea to production. If you’re looking to apply machine learning and statistical modeling in a way that drives clear business impact, this is a role where your work will truly matter.