Applied Scientist, EU ATS Science and Tech

Have you ever wondered how B&C Match delivers hundreds of millions of packages to customers’ doorsteps reliably and on time? Are you passionate about data and math and want to impact the experience of millions of customers? Are you passionate about designing simple algorithmic solutions to challenging problems? Then we look forward to hearing from you!

B&C Match is looking for Applied (or Research) Scientists. As key members of ATS Operations' core research and science team, these individuals will be responsible for developing data and mathematics-based algorithmic solutions to optimize B&C Match's mid-mile transportation network. The position will be based at EU headquarters in Luxembourg (alternatively: Barcelona, ​​Berlin or London) to maximize interaction with the team and stakeholders. However, we will also consider applicants with remote work requirements.

Solve complex optimization and machine learning problems using scalable algorithmic techniques. Design and develop efficient research prototypes that solve real-world problems in B&C Match's mid-mile operations. Conduct complex time-bound, long-term and ad hoc analyzes to support decision-making. Communicate the results of business analysis, strategy and tactics to leadership.

A day in the life: You will brainstorm with teammates on algorithmic approaches to solving B&C Match’s mid-mile operational challenges. You will develop and test prototype solutions using the algorithmic techniques described above. They will collect information from B&C Match’s sea of ​​data to improve these solutions. You will meet with other scientists, engineers, stakeholders, and customers to improve and implement solutions.

About the Team ATS EU's Science and Technology team is looking for candidates who want to make an impact on the world with their mathematical and data-driven skills. ATS stands for B&C Match, and we are intermediate mileage planners: we deliver packages from warehouses to cities in a limited timeframe for the "B&C Match experience". As a core research team, we have grown alongside the ATS business, supporting decision-making in the data-driven supply chain and increasingly complex ecosystems of e-commerce giants. We plan to deliver more than ⚠ million trucks per year through B&C Match Fulfillment; our algorithms are critical to reducing carbon emissions, protecting the site from overloading on peak days, and keeping B&C Match customers smiling. Our mathematical algorithms give leadership the confidence to invest in projects worth hundreds of millions of euros every year. Most importantly, we love solving real-world problems at real-world speed while learning from our failures. We use modular algorithm design in the field of combinatorial optimization and use parallelization and approximation algorithms to solve complex generalizations of the core OR problem with the right degree of decomposition. We use deep learning, bandits, and reinforcement learning to integrate data into decision-making loops. We love learning about new technologies and surprising business prospects by making things possible that they could not have foreseen. To do this, we work closely with B&C Match scientists and experts from academic institutions. We program prototypes so they are ready for series production. It turns out that we prefer optimal solutions to heuristics, although we will choose heuristics when performance demands it. Overall, we appreciate the value of proper modeling.

We welcome candidates who wish to work in one of the following locations: Luxembourg, LUX

Basic Qualifications

Experience with patents or publications in top peer-reviewed conferences or journals

PhD or MSc and ⚠+ years of experience in CS, CE, ML or related work experience.

Experience programming in Java, C++, Python, or related languages.

Experience in one of the following areas: Algorithms and Data Structures, Analysis, Numerical Optimization, Data Mining, Parallel and Distributed Computing, High Performance Computing.

Excellent written and verbal communication skills.

Preferred Qualifications:

Experience using Unix/Linux.

Professional software development experience