Vacant job

Our Applied Scientists at Wolt design and deploy machine learning and applied science solutions that tackle some of our most complex business challenges. By leveraging advanced techniques like statistical analysis, machine learning, deep learning, and operations research, they enhance key processes across Wolt's platform and business operations, creating measurable impact in all 28 countries where we operate.

As an Applied Scientist, you’ll take ownership of use cases within a product development team—from identifying high-value opportunities to developing, prototyping, and deploying solutions, and ensuring they continuously improve in production. We work with a range of technologies, including Python, SQL, Snowflake, Flyte, MLflow, and Seldon Core, and always strive to improve our tooling and ways of working, to support rapid experimentation and innovation.

We’re seeking an Applied Scientist to join our cross-functional Inventory Routing and Replenishment team within the Merchant Group. The team works on developing tooling for our Merchants and Wolt Markets to efficiently manage their inventory. In close collaboration with software engineers, product managers, designers, and analysts, you’ll develop algorithms and data-driven products, such as demand forecasting and inventory optimization solutions, that empower our Merchants to automate and optimize their retail inventory processes. You’ll get to work with forecasting, machine learning and statistical modeling to have a clear business impact in providing better customer experience by improving inventory availability and increasing procurement efficiency. In addition you will also work on developing insights for Merchants to help efficiently manage inventory.

Our humble expectations

We’re looking for an Applied Science enthusiast who is passionate about using data science to make a measurable impact. Here’s what we hope you bring:

• Passion for Applied Science: You identify as a problem solver who loves leveraging data science and machine learning 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.
• 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 (Flyte, Docker, AWS).
• Clear Communication: You can effectively communicate complex technical concepts to non-technical audiences, bridging the gap between data 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.

If you’re driven to make an impact through innovative machine learning solutions, we’d love to see how you can help us push boundaries!