Data Science Intern

Empower Your Future: At MetOx International, we're pioneering the next era of energy security and abundance through breakthrough superconducting technology. As a Data Science Co-op/Intern, you'll join a dynamic team committed to strengthening the world's energy systems to make them more resilient, efficient, and reliable.

Based at our global headquarters in Houston, TX, the Data Science Co-op/Intern supports data-driven decision-making across our operations. This intern role focuses on collecting, analyzing, and interpreting complex data sets, including process and operational data, to help improve our production processes, optimize resource allocation, and enhance product performance. You will use modern data science tools, including AI-assisted development environments and large language models, to move faster while still checking that results are accurate and useful. This position reports to the Chief Information Officer.

Key Responsibilities

Data Collection & Analysis

• Assists in gathering, cleaning, and preprocessing data from multiple sources including relational databases, process historians, sensors, and operational systems to ensure data accuracy and completeness.
• Assists in conducting exploratory data analysis (EDA) to identify patterns, trends, and relationships within production and operational data.
• Assists in troubleshooting data retrieval issues, including network connectivity errors, permission issues, and data access failures from industrial and enterprise data sources.
• Supports data ingestion from industrial protocols such as MQTT and OPC-UA, including a basic understanding of how these protocols communicate process and sensor data.

Modeling, Machine Learning & AI

• Assists in developing and implementing statistical and machine learning models to solve operational challenges such as predictive maintenance, anomaly detection, and process optimization.
• Uses AI-assisted development tools (for example, Cursor or similar coding assistants) and large language models to accelerate coding, data exploration, documentation, and reporting.
• Supports the application of AI tools and techniques, including generative AI and LLMs, to speed up analysis, automate reporting, and surface insights from complex process datasets, while validating model output before it is used in analysis or recommendations.
• Collaborates with engineering and production teams to deploy data-driven solutions that improve efficiency and quality.

Reporting & Visualization

• Creates data visualizations and dashboards to communicate insights and findings to non-technical stakeholders.