Data Scientist, Analytics

Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

Join Crusoe as a Data Scientist, a dedicated hire on our central Data Science and Engineering team. This full-time position offers you the opportunity to own the data and analytics function for key parts of the business, starting with the Data Center Infrastructure Group (DIG) -- the arm of Crusoe that builds and operates data centers, spanning real estate, energy, construction, and parts lifecycle management. As part of a central team, you will also have the opportunity to partner with other groups across the company as needs arise.

You will partner directly with business stakeholders, translate their needs into analytical work, and own the reporting and data quality that leadership depends on for high-stakes decisions.

• • Background in construction, manufacturing, supply chain, or other operationally complex industries.

  • Experience with ERP systems (SAP, Oracle, Sage Intacct, or similar) and the data that flows from them.

  • Familiarity with master data management concepts and cross-system entity resolution.

  • Experience working in a fast-growing company where processes are still being built.

  • Python for data analysis is a plus but not required.

  • Experience with AI-assisted coding tools (e.g., Claude Code, Cursor, GitHub Copilot) to accelerate analytical work.