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.
About the role
Fundamental is seeking a Principal Forward Deployed Data Scientist - Oil & Gas, Houston to facilitate the adoption of NEXUS and collaborate with customers to address complex technical challenges with an initial focus on Houston-based Oil & Gas customers.
The Principal Data Scientist is an integral part of our FDE team, which is dedicated to driving the successful deployment of Fundamental products and proving value over legacy baselines or net new use cases. They work hand-in-hand with customers from the Proof of Value stage to post-implementation, ensuring our solutions run securely in the client's production heartbeat.
In this role, you’ll manage customer relations involving multiple stakeholders (IT, C-suite, and data science teams) and function as a key bridge, translating field insights into our product roadmap.
Key responsibilitiesYou'll individually help deploy into production use cases with considerable business impact, moving from "science experiments" to definitive ROI
You’ll work on rigorous head-to-head benchmarking against client baselines (XGBoost, LightGBM), executing the work of data engineering, feature engineering, and validation
You’ll work in collaboration with our research and product teams to translate operational pain points and data anomalies into essential inputs for the Fundamental roadmap
You’ll be involved in technical strategy to identify the right business problems, prevent data leakage, and handle the "last mile" integration (VPC, on-prem, air-gapped)
Your collaboration with the Sales and Solution Architect teams will help align diverse stakeholders and explain predictions to business users
You hold a PhD / master in CS / Math / Stats or you have equivalent deep statistical literacy
You have 7+ years as a technical individual contributor in Data Science, Machine Learning, Applied Science, or ML Engineering
You have strong experience working directly with customers or business stakeholders, ideally in complex enterprise or industrial environments
You have experience with containerization (Docker), orchestration, and writing performant APIs (FastAPI/Flask)
You master the end-to-end pipeline, from framing, pre-processing, ml algorithm and validation strategies
You have a deep understanding of data handling (PySpark, Pandas) and memory optimization
You have demonstrated experience optimizing models for a specific business problem
You hold strong communication skills with an ability to translate architectural nuances into clear business value
Experience with PyTorch and cloud-native ML pipelines (AWS, GCP, Azure)
Prior experience or understanding of Oil & Gas, energy, utilities, industrials, logistics, or heavy asset environments
Experience as a Forward Deployed Engineer, Staff Engineer, Machine Learning Engineer, or Staff Data Scientist
Industry-based subject matter expertise
Competitive compensation with salary and equity
Comprehensive health coverage for you and your dependents, including medical, dental, vision, and 401K
Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
Relocation support for employees moving to join the team in one of our office locations
A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
Skills Required
- PhD or master's degree in Computer Science, Mathematics, or Statistics, or equivalent deep statistical literacy
- 7+ years of experience as a technical individual contributor in Data Science, Machine Learning, Applied Science, or ML Engineering
- Strong experience working directly with customers or business stakeholders, preferably in complex enterprise or industrial environments
- Experience with containerization using Docker
- Experience with orchestration
- Experience writing performant APIs using FastAPI or Flask
- Expertise across the end-to-end machine learning pipeline, including problem framing, preprocessing, algorithms, and validation strategies
- Deep understanding of data handling with PySpark and Pandas, including memory optimization
- Demonstrated experience optimizing models for specific business problems
- Strong communication skills and ability to translate architectural nuances into clear business value
- Experience with PyTorch
- Experience with cloud-native machine learning pipelines on AWS, GCP, or Azure
- Prior experience or understanding of Oil & Gas, energy, utilities, industrials, logistics, or heavy asset environments
- Experience as a Forward Deployed Engineer, Staff Engineer, Machine Learning Engineer, or Staff Data Scientist
- Industry-based subject matter expertise
What We Do
For decades companies have relied on archaic tools to inform decisions and make bets on the future. Until now. Fundamental empowers businesses to turn gambles into guarantees and determine their future with far greater accuracy than ever before. Built by DeepMind alumni and trusted by Fortune 100 enterprises, NEXUS is our most powerful Large Tabular Model (LTM). By revealing the hidden language of tables, NEXUS unlocks trillions of dollars of value by giving businesses the Power to Predict™.









