Research Data Scientist

About the Company

Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions.

Responsibilities

• Identify, characterize, and evaluate high-value data sources including real-world, synthetic, SCM-generated, and simulator outputs
• Design and analyze synthetic data generation approaches based on Structural Causal Models and probabilistic models
• Work with researchers to define metrics for synthetic dataset usefulness, realism, and causal meaningfulness
• Build tools and workflows to generate, validate, benchmark, and iterate on synthetic datasets at scale
• Develop metrics and evaluation procedures for synthetic data quality
• Transform structured, unstructured, and simulated data into formats suitable for large-scale ML model training
• Collaborate with engineering and infrastructure teams to ensure scalable and robust data workflows

Requirements

• Experience with synthetic data generation for machine learning, specifically for structured or tabular data
• Expertise in Structural Causal Models, causal graphs, causal inference, or probabilistic modelling
• Experience identifying and evaluating high-quality data sources for ML training
• Ability to design quantitative analyses to assess data quality, realism, diversity, and bias
• Strong fundamentals in statistics, probability, and applied machine learning
• Proficiency in Python data processing and scientific computing stacks (numpy, pandas, scipy, scikit-learn)
• Experience with software engineering for research-grade and production-grade data workflows

Preferred Qualifications

• BSc, MSc, or PhD in a quantitative field such as Computer Science, ML, Statistics, Mathematics, or Physics
• Contributions to open source ML, causal inference, or simulation projects
• Experience with SCM libraries, probabilistic programming frameworks, or simulation environments
• Experience working with tabular data and predictive analytics