Data Scientist

About Moment Energy

Independent energy is here. Help us deploy it.

Energy should be free.  Free from aging grids, fragile supply chains, and unnecessary extraction. At Moment Energy, we’re building a world where clean power is abundant, affordable, and uninterrupted for everyone.

The world doesn’t need another promise about energy; it needs proof that a freer future is possible. Moment Energy is the pragmatic liberator of power, the only company certified to turn the largest untapped energy supply into independent energy.

Now is the moment. While the industry scraps millions of batteries with decades of life left, we put them to work by repurposing large-format batteries into advanced battery energy storage systems that deliver real-world impact.

We were told second-life batteries would never be safe enough or scalable enough. We didn’t argue, we engineered the solution. Today, Moment Energy delivers 5x the energy density and holds the certifications required to deploy energy independence at scale.

Now is the moment. Join us.

The Opportunity

We are looking for a Data Scientist Co-op to join our Engineering team starting in January 2027. In this role, you will support the development of advanced models and analytics that improve the performance, reliability, and longevity of our battery energy storage systems.

You will work closely with the Battery Engineering and Battery Management System (BMS) teams to analyze battery data, develop machine learning models, and build tools that transform large datasets into actionable insights. This is an excellent opportunity for a student interested in applying data science and machine learning to real-world energy systems.

Responsibilities and Duties

• Assist in developing and validating battery state-of-charge (SOC) and state-of-health (SOH) estimation algorithms
• Support the development of adaptive battery models using machine learning methods, such as Gaussian Process Regression
• Build automated data analysis tools to process battery data from internal testing labs and external customers
• Develop dashboards and visualization tools to monitor battery performance and operational metrics
• Create AI/ML models to forecast battery load and performance using historical operational and environmental data
• Analyze large datasets from battery testing and operational systems to identify patterns and insights
• Document methodologies, models, and results through well-structured Python code, reports, and presentations
• Collaborate with engineering teams to integrate data-driven insights into product development and system optimization