In this role, you will:
- Support the Purchasing product team as the data science expert, strengthening the team's ability to tackle its most complex purchasing problems.
- Work on central warehouse ordering and related order models, including linear optimization problems such as truck-fill optimization and multi-supplier scenarios.
- Apply algorithms, optimization, and broader data science methods to real purchasing problems, not just theoretical modeling.
- Work in the same operating model as other product teams — combining product development with customer projects and implementation work.
- Use AI tools as part of your day-to-day work.
- Engage directly with customers, communicating clearly and taking a consultative, pragmatic approach — solutions need to work for the customer in practice, which can mean something different from the theoretically "perfect" solutions.
You will thrive if:
- You have concrete, hands-on experience applying mathematical methods, optimization, and/or machine learning to real-world problems — not just coursework or theory.
- You're comfortable and capable in Python, with a hands-on, builder's mindset.
- You have deep ownership and strong command of data science methods
- You're genuinely interested in solving real problems pragmatically, with strong communication skills for working directly with customers; a consultative mindset is a plus.
- You're fluent in English.
- You can work anywhere in Europe; some overlap with US east coast working hours is a nice-to-have, not a requirement.
- You're available to start as soon as possible, backfilling a team member moving to another team in about a month, and can commit to 80–100% allocation (100% preferred).
- Nice to have: Your educational background is in a demanding quantitative field — mathematics, computer science, physics, or similar — which tends to be a good signal here, though this isn't a hard requirement.
This assignment supports a Purchasing product team working on both product development and direct customer implementation projects, with a "Product Engineer" title in line with the team's existing structure. It's expected to start ASAP, with allocation at 80–100% (100% preferred), fully remote within Europe.