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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. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
Key responsibilities
As part of the Research team,
you will contribute to the development of breakthrough machine learning models by working on one of the most important frontiers in model training and evaluation: high-quality real and synthetic data.
This role is especially focused on synthetic data generation, Structural Causal Models (SCMs), and realistic simulation-based data sources. You will help us design, evaluate, and scale datasets that capture the structure, dependencies, and edge cases needed to train foundation models for enterprise tabular data.
The main responsibilities of this role are:
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- Identifying, characterizing, and evaluating high-value data sources for training and evaluating ML models, including real-world data, synthetic data, SCM-generated data, and physical or systems-based simulator outputs
- Designing and analysing synthetic data generation approaches based on Structural Causal Models, probabilistic models, simulators, and other mechanisms that capture realistic relationships between variables
- Working with researchers to
📌 Research Data Scientist (Barcelona)
🏢 Fundamental
📍 Barcelona
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