Applied Scientist, Data Science

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.

Prove the model on their hardest problems. Run projects on real customer data: choose the right framing, build the evaluation harness, benchmark rigorously against strong incumbents, and report results honestly. When numbers look off, get to the root cause rather than tuning past it.

Push beyond the defaults. Where out-of-the-box is not enough, unlock more; fine-tuning, feature engineering, ensembling, in-context learning strategies, calibration, interpretability. Turn one-off wins into reusable workflows and tooling that every future engagement builds on.

Shape what we build next. You are the highest-signal channel between what customers actually hit and what we ship. Turn field learnings into reproducible findings, benchmarks, and roadmap input, for the next generation of TabPFN, and for the products and tooling that make it usable in the real world..

What We're Looking For

• 3+ years of hands on experience with ML/AI in industry, competitive ML, or open-source.

• Strong proficiency in Python and the modern data science ecosystem, with hands-on experience training and deploying deep learning models in PyTorch, including modern deep learning - architectures (especially transformers)

• Ability to translate complex technical concepts into tangible value for both technical and non-technical audiences

• Strong customer-facing skills, with the ability to independently drive technical conversations and engagements across pre-sales, POCs, and post-sales.

• Strong problem-solving skills, with the ability to quickly understand unfamiliar customer problems and translate them into practical data science/ML solutions.

• Broad ML knowledge and the ability to quickly adapt to new domains and problems.

• Strong communication and collaboration skills.

Nice to Have

• Master’s or PhD in a quantitative field.

• Kaggle Grandmaster, Master, or Expert status

• Experience in technical consulting, solutions engineering or forward-deployed roles

• Experience with PyTorch, transformers, tabular data, or other modern ML approaches.

• Contributions to open-source projects, technical writing, talks, or workshops.

US Benefits

• SAP RSUs (Publicly traded, liquid once vested)

• 20 days paid vacation

• Health, dental and vision 100% employer-paid

• Fitness and transportation allowances

• 401k matching (2%, one-year cliff)

• Opportunity to publish your work

• Team offsites at least once a year

• Visa and relocation support (if required)