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.

• 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.

• 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

• 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

• 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

• 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

• Celebrations Throughout the Year: We mark occasions and holidays all year long with team events including holiday parties, team dinners, bowling nights, go-karting, Annual Summer BBQ, golf tournaments, and more.
• Learning & Growth: Lunch and learns, crossword challenges, and education-funding programs to keep you sharp and growing in your career.
• Giving Back: Our Employee Initiatives Committee (EIC) organizes food drives and fundraising for local charities throughout the year – and everyone is welcome to get involved.

• Background Check: As part of our hiring process, the successful candidate will be required to complete a background check, which may include a criminal record check, credential verification, and a driver's abstract (if applicable). Professional references will also be collected as part of the process.
• Assignment: Shortlisted candidates may be asked to complete a practical technical assignment. This is an opportunity to demonstrate how you frame an optimization problem, build your model, and validate results against real-world data.

We respect your time and will provide clear instructions and reasonable timelines for any assignments requested.
Referral Bonus: Do you know someone who would be a great fit for our team? We are offering a CAD $2,500 referral bonus for successful referrals that lead to a hire for this role, effective until further notice. Please connect with Jenny Dong at [email protected]
Artificial Intelligence Disclosure
Rodan Energy may use artificial intelligence tools to support the screening, assessment, or selection of applicants during the recruitment process.
Vacancy Status: This posting is for an existing vacancy.
Rodan Energy Solutions is committed to an inclusive, accessible recruitment and employment experience in compliance with the Accessibility for Ontarians with Disabilities Act, 2005 (AODA). Accommodation is available upon request throughout the hiring process and, if hired, during employment. If you require an accommodation, please contact [email protected] so we can work with you to meet your needs in a manner that respects dignity, independence, integration, and equal opportunity.