data scientist

About Us: At Rodan Energy, our mission is Making Sustainable, Attainable .

As a leading North American energy services company, we provide innovative energy solutions that help clients reduce energy costs and GHG emissions, support electrification, and enhance grid efficiency.

With over 20 years of expertise, we’re trusted by North America’s largest energy users, power producers, and utilities.

Why Join Rodan:

• Thriving Industry : Join a rapidly growing sector at the forefront of innovation and sustainability, shaping the future of energy management.
• Product Market Fit : With a 98% client retention rate and consistent YOY growth, Rodan has built a reputation for delivering trusted, long-term partnerships with industry leaders.
• Top Talent & Strong Culture : Collaborate with high-performing, passionate individuals who are committed to excellence and sustainability.

What Makes This Role Great:

• Direct, Measurable Impact: Your models directly drive customer savings by maximizing battery and price-responsive load (PRL) performance against market price signals and events.
• Built for Growth: Rodan is building out its central data platform to support a goal of 10x revenue growth in 5 years, centered on energy market optimization across IESO, AESO, PJM, NYISO, MISO, and ERCOT.
• Modern Data Stack: Work in Databricks (notebooks, MLflow and Unity Catalog Model Registry, serverless compute) with real market and meter data.
• Structured Ramp-Up: In your first weeks, you'll shadow an external battery optimization build to learn the problem space, provide input, and prepare to take over the project.

Key Responsibilities:

• Build and own optimization models for battery and PRL performance, maximizing value against day-ahead and real-time (DA/RT) price signals, demand response events, and coincident peaks
• Take ownership of the battery optimization project following an initial shadowing period with the external build team
• Backtest optimization models against historical market and meter data to validate performance before deployment
• Track experiments and backtest results systematically in MLflow so model iterations are comparable over time
• Partner with forecasting data scientists to integrate their forecasts as inputs to your optimization models
• Partner with Data Engineering on the quality of the data your models depend on
• Support the expansion of battery and PRL optimization from IESO into AESO, PJM, NYISO, MISO, and ERCOT

Required Skills and Qualifications:

• Degree in Operations Research, Applied Math, Statistics, or a related quantitative field, or equivalent industry experience (MSc or PhD preferred)
• 3+ years of hands-on experience building optimization models (mathematical programming, mixed-integer programming, or control-theory approaches) in a production or applied research setting
• Demonstrated experience backtesting models against historical data and tracking experiment and backtest results systematically (MLflow or a comparable experiment-tracking tool)
• Strong Python and SQL skills, including processing large time-series datasets
• Experience translating a real-world operational problem (asset dispatch, resource allocation, scheduling) into a mathematical model
• Ability to work independently in an early-stage, ambiguous environment

Preferred Qualifications:

• Hands-on experience with Databricks; Databricks certification is an asset
• Experience with energy markets, battery storage, or demand response programs
• Familiarity with commercial or open-source solvers (Gurobi, CPLEX, or similar)
• Experience partnering with data scientists who build forecasting models used as inputs to optimization

Rodan Role, Compensation & Benefits Include:

• Hybrid: 3 days in office in Mississauga, Ontario
• Profit sharing Plan
• Comprehensive health benefits package
• Group RRSP with employer matching
• Base salary range of CAD $110,000 to $130,000

Life at Rodan – Our Culture:

At Rodan, we believe