Who we are

Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched, until now. What LLMs did for language, we're doing for tables.

We pioneered tabular foundation models: TabPFN v2 was a Nature cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi. The hardest problems - millions of rows, real-time inference, entirely new modalities - are still open, and no one else is working on them at this level.

We're a small, highly selective team of 40+ with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN, led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by Bernhard Schölkopf and Turing Award winner Yann LeCun.

In July 2026, less than 18 months after our €9M pre-seed, we joined SAP as an independent frontier AI lab - same team, mission, and open-weights models, now backed by more than €1 billion over four years.

About The Role

You will join our data science team working at the frontier of tabular foundation models. As an Applied Data Scientist you sit between our tabular foundation models and the hardest problems customers bring to them. You take real customer data, an insurer's claims history, millions of card transactions, or proteomic blood panels for early cancer detection, and drive what TabPFN can unlock. You guide teams from the first discovery call through demos, POCs, and hands-on support all the way to production. Along the way you compare solutions against strong baselines, push results further with new workflows, and uncover strengths and weaknesses, feeding what you learn back to the model team and shape the next generation of TabPFN.

How You'll Drive Impact:

Guide customers to success with TabPFN. Own engagements end to end: discovery calls to understand the problem, technical demos tied to real business objectives, onboarding that delivers quick wins, and hands-on support as teams move from POC to production. Present results and capabilities so they land, a POC result that gets the green light, a demo that makes the value obvious. You will be in the room with their data scientists and their decision-makers, and you can hold your own with both.