Data Scientist

• Partner with nuclear engineering teams to develop, refine, and scale large-scale models that strengthen engineering analysis, decision-making, and predictive insight.
• Build and maintain analytical models supporting engineering decisions across workforce and schedule forecasting, simulation result aggregation, supplier and supply-chain analytics, and reliability and risk modelling.
• Develop reproducible data pipelines that pull from MBSE/PLM, SPDM, schedule, ERP, and simulation output systems and serve cleaned datasets to downstream tools.
• Produce dashboards, briefings, and technical memoranda that translate analysis into decisions for engineering leadership and program management.

This role directly supports the development and deployment of advanced nuclear reactors that provide clean, firm heat and power, contributing to climate change mitigation and energy sustainability.

• Master's or PhD in a quantitative field (statistics, applied mathematics, physics, engineering, computer science, operations research), or a bachelor's with equivalent applied experience.
• 2 or more years of experience building analytical models or data pipelines used in a production or operational setting.
• Proficiency in Python (pandas, NumPy, scikit-learn) and SQL.
• Experience with statistical modelling (regression, time-series, Bayesian inference, uncertainty quantification, optimization, or simulation based methods).

• Extended Healthcare Plan
• Vacation policy designed to support work-life balance
• EAP Programs
• Wellness Subsidy
• Annual Performance Review
• Paid Volunteer Days
• Career development opportunities

Terrestrial Energy is a US developer of advanced, Generation IV nuclear reactors, specifically the Integral Molten Salt Reactor (IMSR) small modular nuclear plant, aiming to provide cost-competitive, clean firm heat and power to industry.