Senior Data Scientist, Research Engineer

About This Role

Join Crusoe Energy as a Senior Data Scientist, an early and pivotal hire on our growing central Data Science and Engineering team. This full-time position offers you the unique opportunity to drive significant impact across product analytics, operations, go-to-market strategies, and capacity planning, playing a key role in Crusoe's mission to meet the ever-increasing demand for AI infrastructure and innovate sustainably.

What You'll Be Working On

• Develop Forecasting & Analysis Models: Build and deploy models for financial forecasting and product analysis to drive strategic decisions.
• Perform Root Cause Analysis & Prediction: Investigate operational incidents and predict failures, implementing solutions for system reliability and efficiency.
• Analyze Cloud Infrastructure Products: Conduct deep analysis of cloud infrastructure product usage and performance to identify areas for improvement and guide feature development.
• Champion Data Quality & Infrastructure: Collaborate with internal teams on initiatives to maintain high-quality data and contribute to the scalable evolution of our modern data infrastructure.

What You'll Bring to the Team

• Analytical Expertise: Demonstrate deep familiarity with core analytical methods including Monte Carlo simulation, predictive analytics, and time series modeling.
• Technical Fluency: Possess proficiency in SQL and Python for data analysis, alongside a strong understanding of current data infrastructure architectures.
• Data Visualization Proficiency: Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker) to communicate insights effectively.
• Commitment to Quality: Show a proven track record and passion for data quality.
• Ownership: As an early hire on the data science team, you'll be expected to act autonomously to drive forward analytics projects.

Bonus Points

• Advanced degree (Master's or Ph.D.) in a quantitative field (e.g., Data Science, Statistics, Computer Science) or equivalent experience.
• Experience building cloud infrastructure (e.g., AWS, GCP, Azure).
• Experience on a growing or early-stage data team, contributing to foundational development.