Research Scientist, Foundational Data Science
Core
Building foundational tools and datasets for tabular foundation models (TFMs) to solve data-science problems across domains.
Role type
Senior individual contributor research scientist (foundational data science)
Builds
Frontier tools extending TabPFN, automated agentic pipelines, and trustworthy benchmarks for structured data
Domain
Artificial Intelligence / Machine Learning / Structured Data / Tabular Foundation Models
Deliverable
production ML models | research
Required skills
Data science across multiple domains, gradient-boosted trees (XGBoost), deep learning, dataset defect analysis (leakage, label noise, distribution shift), foundational research mindset, senior IC autonomy
Preferred skills
Building evaluation harnesses/benchmark suites, LLM- or agent-assisted pipelines, linking external research to internal roadmaps, prior work on tabular/foundation models
Technologies
TabPFN, XGBoost, deep learning frameworks, automated agentic pipelines
Responsibilities
Invent and build frontier tools extending TabPFN, set research direction on model capabilities and benchmarks, bring in external research and customer needs to shape directions, build trustworthy benchmarks from structured data, implement baselines and competitor models, build automated agentic pipelines with human-in-the-loop
Seniority
Senior, hands-on IC