The Nuclear Company is seeking to solve the problem of inefficient and costly nuclear reactor construction by leveraging advanced technology and AI/ML capabilities to streamline execution and improve safety.
Requirements
- Machine Learning: Deep expertise in AI/ML systems, including supervised and unsupervised learning, time-series analysis, and anomaly detection
- Programming: Advanced proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn) for model development and deployment
- Data Platforms: Familiarity with machine learning frameworks and model deployment; experience with Palantir Foundry or similar data integration platforms preferred
- Analytics & Visualization: Strong skills in data analysis, statistical modeling, and data visualization tools
- Model Operations: Experience with MLOps, model versioning, monitoring, and continuous training pipelines
- Big Data: Experience working with large-scale datasets and distributed computing frameworks
- Experience with predictive analytics, anomaly detection, and optimization algorithms
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
Other
- 7-12 years of experience in data science, machine learning, or advanced analytics
- Proven track record of developing and deploying production ML models at scale
- Strong analytical and problem-solving skills with ability to translate business problems into data science solutions
- Excellent communication skills to explain complex technical concepts to non-technical stakeholders
- Ability to work independently and lead data science initiatives
