Join Prior Labs! Who We Are: Prior Labs is building breakthrough foundation models that understand spreadsheets and databases—the backbone of science and business. Foundation models have transformed text and images, but structured data has remained largely untouched. We’re tackling this $100B opportunity to revolutionize how we approach scientific discovery, medical research, financial modeling, and business intelligence. Our Impact: We aim to be the world-leading organization working on structured data. Our TabPFN v2 model, recently published in Nature, sets the new state-of-the-art for small structured data. Our models have gained significant traction with 1M downloads and 3,500 GitHub stars. We are now building the next generation of models that combine AI advancements with specialized architectures for structured data. Backing and Momentum: With €9M in pre-seed funding from top-tier investors including Balderton Capital, XTX Ventures, and Hector Foundation—and support from leaders at Hugging Face, DeepMind, and Silo AI—we’re moving rapidly toward commercialization. Read more about our vision on our blog. About The Role You'll be among the first data scientists working with an entirely new class of AI models. As our Founding Data Scientists, you'll be the critical link between our breakthrough technology and real-world applications. As a super-user of our foundation models, you'll deeply understand our technology's capabilities, demonstrate compelling use cases, and help shape our product roadmap. In this multifaceted role, you'll wear several hats and connect different aspects of our business. Here's how you'll drive impact across key areas: Be a Power User & Tinkerer: Dive deep into our novel TFMs (like TabPFN), experiment relentlessly using unique capabilities like ICL, and uncover new applications. Demonstrate Groundbreaking Value: Build compelling proof-of-concepts showing how native tabular AI solves problems traditional methods can't. Shape Agentic Data Science: Contribute hands-on to our vision of AI as a true reasoning partner for automated discovery. Join at the Perfect Time: Make a significant impact in a well-funded startup with strong momentum. How You'll Drive Impact: Applied Data Science & Experimentation: Identify high-impact use cases; build compelling PoCs/demos showcasing TFM advantages; develop best-practice workflows; benchmark rigorously. Customer Success: Engage users to understand challenges; showcase TFM value via technical demos linked directly to user business objectives; guide onboarding for quick wins using ICL; translate feedback into technical insights. Community & Education: Design/deliver engaging workshops/tutorials; create content explaining the TFM paradigm shift vs. LLMs/traditional ML; empower community members (Kaggle, GitHub); share your enthusiasm and findings. What We're Looking For: Passionate Tinkerer & Power User: Deep curiosity for hands-on exploration of cutting-edge AI (PFNs, ICL, native architectures). Proven Data Scientist: PhD/Masters in a quantitative field 3 yrs experience building/deploying ML/AI (industry, Kaggle, open-source). Technical Expertise: Deep Python & data science ecosystem knowledge; strong software engineering practices. Communicator: Ability to translate complex tech into tangible value and explain concepts clearly. Excitement for our Mission: Driven to solve fundamental AI problems for structured data. What Makes You Special (Bonus Points): Kaggle: Grandmaster/Master/Expert status. Experience: Technical Consulting, Solutions Engineering, MLOps, Developer Advocacy. Contributions: Open-source libraries, data science tools. Portfolio: Blog posts, talks, projects showcasing technical communication. Location Offices in Freiburg, Germany - a university city at the edge of the Black Forest, Switzerland and France, and Berlin—a global tech hub and one of Europe’s most dynamic cities Benefits Competitive compensation package with meaningful equity 30 days of paid vacation public holidays Comprehensive benefits including healthcare, transportation, and fitness Work with state-of-the-art ML architecture, substantial compute resources and with a world-class team