Data Science Co-Op​/Intern Summer

At Met Ox 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.

• 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.

• 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.

• Creates data visualizations and dashboards to communicate insights and findings to non-technical stakeholders.
• Prepares reports summarizing data analysis results, with clear recommendations based on data insights.
• Uses AI-assisted writing and coding tools to draft reports, queries, and visualizations, then reviews and corrects the output before sharing it.

• Works with cross-functional teams to understand business needs and translate them into data science objectives.
• Stays current with industry trends, tools, and best practices in data science, AI-assisted development, large language models, and industrial data systems.
• Other duties as assigned.

• Actively enrolled in a bachelor's degree (sophomore standing or above) in data science, statistics, computer science, engineering, or a related field.
• Prior exposure to data science, data engineering, or a related field through coursework, personal projects, or other relevant experience.
• Actively enrolled in a bachelor's degree in data science, statistics, computer science, engineering, or a related field at an accredited university.
• Basic understanding of networking concepts, including TCP/IP, DNS, HTTP/HTTPS, and general connectivity troubleshooting.
• Basic familiarity with relational databases such as PostgreSQL or MySQL, including writing simple queries (SELECT, JOIN, WHERE).
• Basic understanding of AI-assisted development environments (for example, Cursor or similar coding assistants) and of large language models, including how these tools are used to write, review, and debug code and to speed up data analysis.
• Awareness of AI concepts and how they can be applied to data science and analytics workflows, including the need to check model output for accuracy.

• Actively enrolled in a master's degree in data science, statistics, computer science, engineering, or a related field.
• Previous internship or relevant work experience.
• Hands-on experience using an AI-assisted IDE or coding…