The opportunity
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.
What you'll do
Stand Up the Central Team: Work with leaders across the business to understand their analytical needs, and design the staffing and operating model that meets them. Define how analysts are deployed, how work is prioritized, and how the team engages with each domain.
Build and Develop the Team: Recruit and grow analysts and data scientists who pair technical depth with business credibility. Build the career path and development model to retain talent.
Set Standards for Analytical Rigor: Define how the team approaches statistical and modeling work, including experimental design, forecasting, and how uncertainty is communicated to decision-makers. Review your team's methods substantively, and work hands-on where needed.
Build the Data Science Capability: Determine where predictive and statistical methods will have the most impact and sequence the investment accordingly. Near-term opportunities span power utilization, capacity and demand forecasting, schedule and cost forecasting, fleet reliability, and product experimentation.
Own Certified Marts and Metric Definitions: Own the business logic, certified data marts, metric dictionary, and business-rule testing that keep metrics consistent across the company. Establish peer review as a standard practice so work is checked by qualified colleagues before it reaches business leaders.
Own Executive and Cross-Business Reporting: Own certified reporting for the executive team, the board, and questions that span business units, with operational reporting in the business units built on the marts your team certifies.
What they're looking for
- Drive High-Stakes Decision Support: Turn the company's most complex, cross-functional questions into clear analysis and recommendations that leadership can act on.
- Build Toward Self-Service: Create the conditions for the business to answer routine questions without routing through an analyst, including the table and field descriptions our data MCP reasons over, on top of certified marts with properly defined metrics.
- Maintain Close Proximity to the Business: Keep analysts embedded in their domains through staff meetings, planning cycles, and shared goals, and align central and business unit priorities so analysts always know what matters most.
- Partner with the Data Team: Collaborate with the Data team on the data foundation, contributing the domain context and business definitions that help new source systems and data models land well for the business.
