- Location
- Prague
- Workplace
- Hybrid
- Department
- Development
- Source
- Lever
Description
- Pioneering Technology: At Coupa, we're at the forefront of innovation, leveraging the latest technology to empower our customers with greater efficiency and visibility in their spend.
- Collaborative Culture: We value collaboration and teamwork, and our culture is driven by transparency, openness, and a shared commitment to excellence.
- Global Impact: Join a company where your work has a global, measurable impact on our clients, the business, and each other.
About The Team
Rossum joined Coupa earlier this year. We brought the document understanding layer - our proprietary T-LLM (transactional LLM) architectures, which we design and train from scratch, and which read the world's messiest business documents in production, millions of them every week. Now we are pointing the same in-house research capability at a much bigger problem: not just reading the documents, but acting on them.
About the Role
Sourcing is where the money is actually decided.
We are expanding our Data Capture Research team in Prague with a Senior Data Scientist to work on Sourcing.
Which suppliers get invited. How the event is structured. How bids that differ in price, lead time, quality, risk and carbon get compared at all. What a fair price even is. When to award, to whom, and how to split the award across suppliers.
For a researcher this is unusually open ground - not one model family, but several, on the same data:
- Recommendation and retrieval. Supplier discovery: matching demand to the right suppliers across a 10M-node network.
- Forecasting and should-cost modelling. What this category, in this region, at this volume, should cost right now.
- Game theory and mechanism design. Auction formats, bidding behaviour, incentives, and competitive dynamics between real counterparties.
- Combinatorial optimisation. Award allocation under volume, capacity and multi-sourcing constraints.
- Multimodal document understanding. RFPs, specs, quotes and contracts carry the actual requirements - and our T-LLM foundations already give us a head start there.
Part of the work is choosing the right instrument for each - neural networks, gradient boosting, optimisation, bandits, mechanism design - instead of forcing one.
Very little of this has been built with modern ML yet. That is the point of the role: real greenfield problems, a dataset nobody else has, and a product that ships to companies whose margins depend on getting these decisions right.
You will work in a small, senior team of researchers and engineers - the group that built Rossum's production models from scratch - with direct access to Product and the AI Platform team. Ideas that work do not sit on paper; they roll into systems used at scale.