Senior Data Scientist

The Nuclear Company is the fastest growing startup in the nuclear and energy space creating a never before seen fleet-scale approach to building nuclear reactors. Through its design-once, build-many approach and coalition building across communities, regulators, and financial stakeholders, The Nuclear Company is committed to delivering safe and reliable electricity at the lowest cost, while catalyzing the nuclear industry toward rapid development in America and globally.

Senior Data Scientist

About The Nuclear Company

The Nuclear Company (TNC) is transforming the nuclear energy sector by streamlining execution, leveraging advanced technology, and fostering a strong culture of safety, quality, and operational excellence.

TNC operates as a fleet-scale nuclear power developer, bringing a disciplined, execution-focused approach to an industry that has historically struggled with cost overruns and schedule delays. By leveraging proven technologies and innovative digital solutions, we're building nuclear plants faster, cheaper, and safer than ever before.

We believe that detailed, executable plans—constantly evaluated and refined—are central to achieving long-term success. Our dedicated teams work in parallel across all phases, ensuring the readiness and smooth execution of the entire project.

About Nuclear OS & AI/ML at TNC

In partnership with Palantir Technologies, TNC is developing Nuclear OS - a secure, AI-native digital platform that serves as an integrated operating system for managing every aspect of nuclear plant construction and commissioning. Nuclear OS is built to be an AI-native platform – meaning advanced analytics and machine learning are woven into its core functionalities rather than being afterthoughts. By leveraging AI/ML, the platform helps project teams make smarter decisions faster, uncover patterns that humans might miss, and automate routine tasks.

Advanced analytics and machine learning algorithms form the "brain" of the system, analyzing data across projects to optimize schedules, flag risks, and improve each new plant based on prior lessons learned.

Position Overview

We're seeking a Senior Data Scientist to join our Nuclear OS team and build the AI/ML capabilities that will transform nuclear construction. This senior-level position offers the unique opportunity to develop predictive analytics and machine learning models that learn from historical and real-time data to predict future outcomes, detect anomalies, and optimize nuclear project delivery. You'll work with cutting-edge AI/ML technologies and data integration platforms, deploying models that directly impact the efficiency, safety, and cost-effectiveness of fleet-scale nuclear deployment.

 Key Responsibilities

• Predictive Analytics Development: Host and develop various ML models that learn from historical and real-time data to predict future outcomes or detect anomalies, including schedule slippage prediction, equipment failure forecasting, and risk assessment
• AI Model Development & Deployment: Develop, train, and deploy machine learning models within the Palantir Foundry environment, managing model development, training, and inference at scale while ensuring models operate on governed, quality-controlled data
• Anomaly Detection & Optimization: Introduce ML algorithms on numeric datasets to identify outliers or predict issues, applying time-series anomaly detection to identify unusual fluctuations that could indicate problems
• Algorithm Optimization: Fine-tune and optimize predictive analytics algorithms to improve the accuracy of fault detection and predictive maintenance, adjusting machine learning models based on historical data to enhance prediction accuracy
• AI-Driven Decision Support: Build AI capabilities that augment human decision-making with AI intelligence, helping project managers identify potential risks before they become problems and enabling real-time adaptation to prevent cost overruns
• Data Analysis & Visualization: Perform comprehensive data analysis and create visualizations that communicate insights to stakeholders, enabling data-driven strategy and decision-making
• Model Training & Continuous Improvement: Train models on historical data from previous construction projects and continuously improve them with incoming data from ongoing projects, scheduling retraining as new data accumulates
• Cross-Project Learning: Develop fleet-wide learning capabilities where data from each project is aggregated to enable performance bench