---
title: 'Applied Scientist, Data Science at Prior Labs'
canonical: 'https://feeny.ai/job/applied-scientist-data-science-prior-labs-new-york-4nt000n2q9sx'
type: 'job'
last_seen: '2026-09-18'
---

# Applied Scientist, Data Science at Prior Labs

- **Company:** Prior Labs
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-06-25
- **Last confirmed live:** 2026-09-18
- **Apply:** https://jobs.ashbyhq.com/prior-labs/f1ea16f3-8414-4ffa-acf8-701577c9c7dc/application

**Skills:** Python, PyTorch, Machine Learning, Artificial Intelligence, Software Engineering, Technical Consulting, Solutions Engineering, MLOps, Open Source Contribution

> Join the data science team to experiment with tabular foundation models, build proof-of-concepts, and demonstrate value to customers. You will work directly with users to guide onboarding, translate feedback into technical insights, and contribute to product roadmap development through technical demos and community...

## Job description

## 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](https://www.nature.com/articles/s41586-024-08328-6) cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production from [detecting lung disease with Oxford Cancer Analytics](https://www.oxcan.org/news/prior-labs-and-oxford-cancer-analytics-partner-to-advance-liquid-biopsy-and-clinical-decision-making-in-lung-disease) to [preventing train failures with Hitachi](https://siliconangle.com/2025/12/01/prior-labs-debuts-tabular-ai-foundation-model-scales-10-million-rows/). 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+](https://priorlabs.ai/about) with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN, led by [Frank Hutter](https://www.linkedin.com/in/frank-hutter-9190b24b/), [Noah Hollmann](https://www.linkedin.com/in/noah-hollmann-668b9010b/), and [Sauraj Gambhir](https://www.linkedin.com/in/sauraj-g/), 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](https://priorlabs.ai/blog-posts/priorlabs-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. 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)

Life at Prior Labs You'll work alongside researchers and builders who hold themselves to a very high bar - in the quality of their work and in how they work with each other. We move fast and still take the time to do things right. Our teams are based in Berlin, Freiburg, and New York - when you're working on something as hard as TabPFN, being in the same room matters. But great people come from everywhere, and in exceptional cases we're open to remote, which usually means frequent travel to one of our offices. Wherever you're based, the whole company comes together regularly for offsites to build and celebrate together.

Our Commitments The best products and teams are built by people with a wide range of perspectives and backgrounds. We welcome applications from all identities and walks of life - especially if you've ever felt discouraged by "not checking every box" - and provide equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are. We care about how your data is handled - see our [Recruiting Data Privacy](https://priorlabs.ai/recruiting-data-privacy) page

## About Prior Labs

## Company Overview
- **One-liner**: Prior Labs builds state-of-the-art tabular foundation models (starting with TabPFN) that natively understand structured data, enabling zero-shot and fine-tuned predictions for spreadsheets, databases, and enterprise data workflows.
- **Entity Type**: Private (Pre-Seed/Seed stage; $9.4M total funding)
- **Headquarters**: Freiburg, Germany (with offices in Berlin, New York, and San Francisco)
- **Founded**: 2024
- **Founders**: Frank Hutter, Noah Hollmann, Alexander Rudolf Diehl, Sauraj Gambhir

## Core Business
- **Primary Industry**: Artificial Intelligence / Foundation Models for Tabular Data
- **Target Customers**: B2B – Data science teams, enterprise data analysts, quantitative researchers, and agent developers in finance, healthcare, energy, and business analytics.
- **Mission / Purpose**: "Help humanity make better decisions" by creating the world’s most capable tabular AI — a foundation for discovery across science, medicine, and the global economy.

## Products & Services
- **TabPFN-3 (API)**: Their frontier model for structured data prediction. Handles up to 1M rows in 0.2 seconds. Features a "Thinking mode" that achieves +420 ELO and beats AutoML in 80% of cases on the TabArena benchmark.
- **TabPFN-3 (VPC / Private Cloud)**: Deploy the same frontier model inside a customer's own cloud environment for sensitive data (healthcare, finance, defense).
- **Agent SDK / Integration**: Embed tabular intelligence into AI agents, enabling structured data reasoning for agentic workflows.
- **Synthetic Data Generation**: Generate high-quality synthetic tabular data for privacy-preserving analytics, model training, or data augmentation.

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed (private company).
- **Key Financials**: $9.4M in total funding (Seed round closed Feb 2025; corporate/pre-seed rounds prior)
- **Notable Investors / Partners**: Balderton Capital, XTX Ventures, SAP Founder Hans-Werner Hector’s Hector Foundation, Atlantic Labs, Galion.exe. Angels include Thomas Wolf (Hugging Face Co-Founder), Peter Sarlin (Silo AI), Guy Podjarny (Snyk/Tessl), Ed Grefenstette (DeepMind), Robin Rombach (Black Forest Labs), and Christopher Lynch (AtScale).
- **Growth Signals**: Headcount grew 320% YoY to ~39 employees (from 7 in 2024). Recent acquisition by SAP (signed definitive agreement in 2025). Active job postings: 22. Operates in 10 countries.

## Competitive Advantages
- **First-mover in "Tabular Foundation Models"**: While LLMs and vision models are saturated, Prior Labs is pioneering large-scale pre-trained transformers for spreadsheets and databases.
- **Breathtaking Performance**: 93% win rate over classic ML on TabArena; beats AutoML in 80% of cases; 0.2s inference on 1M rows — orders of magnitude faster than traditional AutoML pipelines.
- **Scientific Lineage**: Founders and team come from top ML institutions (University of Freiburg, Max Planck Institute, Meta FAIR). Scientific advisory board includes Yann LeCun and Bernhard Schölkopf.
- **Acquisition by SAP**: Signed definitive agreement — provides immediate enterprise credibility, distribution, and resources for scaling.

## Strategic Focus
- **Scale the model**: Continue improving TabPFN-3 with "Thinking mode" and larger context windows for complex reasoning.
- **Enterprise adoption**: Expand into healthcare cancer risk prediction, financial trading, and energy forecasting via VPC deployments.
- **Agent ecosystem**: Make TabPFN the default AI for structured data in agentic workflows (LangChain, AutoGPT, etc.).
- **Post-acquisition integration**: Embed the technology into SAP’s business suite to power predictive analytics for millions of enterprises.

## Why Work Here
- **Cutting-edge AI work**: Work with state-of-the-art foundation model architecture, substantial compute resources, and a world-class team (Google DeepMind, Meta, Hugging Face alumni).
- **Meaningful impact**: Solve real problems in science, medicine, and finance — not just another chatbot.
- **Generous benefits**: 30 days paid vacation + public holidays (paid out if not taken), competitive salary + meaningful equity, seamless relocation support (including relocation bonus), healthcare, transportation, fitness, team lunches & company offsites.
- **Office-first culture, multiple hubs**: In-office policy in Freiburg (academic excellence + nature), Berlin (tech/culture), New York (energy/talent), and San Francisco (innovation epicenter). Strong preference for in-person collaboration with top-tier peers.
- **Team values**: High integrity, high-performance empathetic culture, undogmatic ("valuing output over principles"), and mission-driven.
- **Growth stage**: High growth (320% YoY) + post-acquisition by SAP means accelerated impact, resources, and career development.

## Sources
1. [priorlabs.ai](https://priorlabs.ai/)
2. [priorlabs.ai/careers](https://priorlabs.ai/careers)
3. [priorlabs.ai/about](https://priorlabs.ai/about)
4. [LinkedIn (Prior Labs)](https://www.linkedin.com/company/prior-labs)
5. [Built In (Prior Labs)](https://builtin.com/company/prior-labs)

## Other roles at Prior Labs

- [Head of Partnerships (SAP)](https://feeny.ai/job/head-of-partnerships-sap-prior-labs-new-york-wv4ad00qtrxm) — New York, NY
- [Head of Operations](https://feeny.ai/job/head-of-operations-prior-labs-berlin-5hdrregy1pg4) — Berlin, Germany
- [Technical Product Manager, Integrations](https://feeny.ai/job/technical-product-manager-integrations-prior-labs-berlin-9b8r2w1rk6vs) — Berlin, Germany
- [Director of Engineering](https://feeny.ai/job/director-of-engineering-prior-labs-berlin-kwhgq8ardmsh) — Berlin, Germany
- [Founder Associate (NYC)](https://feeny.ai/job/founder-associate-nyc-prior-labs-new-york-pgwmkf4z47nw) — New York, NY
- [Visiting Associate Cohort](https://feeny.ai/job/visiting-associate-cohort-prior-labs-berlin-74t53y2nb9zq) — Berlin, Germany
- [Founder Associate (Berlin)](https://feeny.ai/job/founder-associate-berlin-prior-labs-berlin-av0j7475f3mz) — Berlin, Germany
- [Partnerships Manager (SAP)](https://feeny.ai/job/partnerships-manager-sap-prior-labs-new-york-ps8a717nst6y) — New York, NY
- [Partnerships Manager (Non-SAP)](https://feeny.ai/job/partnerships-manager-non-sap-prior-labs-new-york-538y9t74bc87) — New York, NY
- [Technical Recruiter (Berlin)](https://feeny.ai/job/technical-recruiter-berlin-prior-labs-berlin-9d9ctmt8a209) — Berlin, Germany