As an experienced data scientist, you extract relevant insights from the amount of data available within Colruyt Group. You build machine learning models for our various retail brands. The result of your work: an even better, tailor‑made service for our customers.
What will you do?
Within the IT division Data & Analytics, you work in a multidisciplinary team consisting of data scientists, data science engineers, data analysts, BI engineers… Together, you provide analytical solutions for the various Colruyt Group brands, such as Okay, Bike Republic, Bio-Planet or Jims. Within the data science knowledge group, experiences and expertise are shared, allowing you to continue learning.
As a data scientist, you collaborate with complementary colleagues on a wide range of projects, working with new techniques and technologies (e.g., Polars, LightGBM, PyTorch, UV, Kedro, Ruff). In addition, we also work with cutting‑edge in‑house technology, such as our own forecasting module or causality module. You are also encouraged to proactively explore new methods and techniques—in consultation with the team—to help expand the knowledge and skill set of the group.
The team focuses on our internal customers, the business partners. We translate their needs into analytical solutions, which we develop in multidisciplinary teams. This results in close and direct collaboration with other IT teams and the business.
We are responsible for identifying new analytics opportunities. We proactively search for insights that create added value for our partners. In doing so, we look not only at Colruyt Group, but also at external trends in analytical use cases and technological innovation.
Colruyt Group consists of many different entities, which creates enormous variety and volume in both data and use cases. The projects you contribute to range from customer segmentation, sales forecasting, and analysis of in‑store experiments to operational efficiency of machines, predictive maintenance, and optimal use of raw materials.
You work in Halle and can work from home up to two days per week.
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