Junior Data Scientist

• A gross monthly salary between €3,900 - €5,100 (based on 40 hours);
• An annual bonus of up to 5% of your annual salary, based on organizational goals;
• 30 paid vacation days (with the option to buy or sell days) and 8% holiday allowance. You build a pension through participation in the Pensioenfonds voor de Levensmiddelenindustrie;
• A travel allowance (€ 0.21 per kilometer with a maximum of 35 kilometers one way). We like to work together in the office, but working partly from home is also possible;
• Room for entrepreneurship, growth, and development. Not only in your role, but also through our Jumbo Academy, online training via GoodHabitz, and with a training budget;
• Daily fresh lunch in our Foodcafé, good coffee, and fresh fruit. You can exercise daily in our own Jumbo Gym for a small fee;
• Colleague discounts such as 10% discount on your groceries (up to €325 per year), participation in our collective health insurance, or discounts via Benefits at Work.

Do you want to know more about our employment conditions? Then click here.

From the very beginning, you will work on challenging projects that test your analytical and interpersonal skills. These projects can be located in all parts of Jumbo, from logistics to marketing and from formula to procurement. You build data science products from start (raw data) to finish (production-ready models). Easily 50% of your time is spent on data preparation, exploration, (advanced) analyses, and even some BI, so it is important that you also enjoy that alongside Machine Learning / building AI Agents. We focus on results, not on output: customers turn into fans through better decisions based on the insights that you discover.

• Analyze large datasets to discover insights that improve decisions in stores, online, and the supply chain.
• Build predictive models that help better forecast store inventory, product demand, and customer behavior.
• Investigate commercial opportunities by analyzing price, promotion, and assortment data.
• Develop data agents, dashboards, and automated reports that your colleagues use daily to utilize your data science products.
• Improve data quality by monitoring data flows and identifying and resolving issues.
• Test, optimize, and implement machine learning models in our production environment.
• Translate complex analyses into understandable advice for colleagues outside of Data Science.
• Deliver direct business impact with models, such as less shrinkage, better availability, or higher customer satisfaction.

• 09.00 - 11.00: You work in DataBricks (PySpark) with our enormous datasets to improve the model that estimates product interchangeability, which plays a key role in selecting the right assortment.
• 11.00 - 12.00: You review the latest results of the machine learning models in your portfolio.
• 12.00 - 12.45: Lunch meeting with your colleagues from DS&A in our Foodcafé.
• 13.00 - 15.00: You perform a peer review of a model developed by a colleague to improve our loyalty offers, using that knowledge to improve our assortment model.
• 15.00 - 17.00: You attend a workshop focused on improving store layout differentiation using a data-driven approach.