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About Rodan Energy Solutions

Rodan Energy Solutions is a prominent North American energy services company with over two decades of expertise in delivering innovative energy solutions aimed at lowering costs and greenhouse gas emissions, promoting electrification, and optimizing grid efficiency. The company is widely recognized among the largest energy users, power producers, and utilities across North America.

Why Join Rodan Energy?

Work in a fast-growing, cutting-edge sector at the intersection of sustainability and energy management innovation.
Benefit from a high client retention rate of 98% and steady growth, evidencing strong product-market alignment and trusted long-term partnerships.
Collaborate within a talented, driven team committed to excellence, innovation, and sustainable development.

Role Highlights

Hands-on experience in developing forecasting models relevant to real-world facility loads, market demands, and electricity pricing.
Exposure to time-series modeling and machine learning pipelines through the Databricks platform within active production settings.
Learning opportunities alongside seasoned data scientists and energy market experts.
Enhance technical acumen in a dynamic, collaborative environment with substantial mentorship.
In-office, full-time engagement to facilitate direct collaboration and guided learning.

Key Responsibilities

Develop, design, and validate time-series forecasting models for facility energy loads, market demand, and electricity price signals.
Investigate and optimize various modeling techniques, including statistical, machine learning, and deep learning methods, considering forecasting horizons, data availability, and accuracy needs.
Participate in machine learning pipeline development on the Databricks platform utilizing tools such as PySpark, MLflow, and Delta Lake; training on platform use provided.
Create dashboards and automated reporting within Databricks to replace existing manual Excel processes.
Learn from domain specialists about market frameworks, tariff regulations, and grid operations to enrich model features and evaluation strategies.
Effectively communicate model outcomes, assumptions, and constraints to audiences with technical and non-technical backgrounds.

Requirements

Enrollment in a recognized Co-op program pursuing an undergraduate or graduate degree in Data Science, Statistics, Computer Science, Engineering, or related quantitative disciplines.
Working proficiency with Python, SQL, Excel, and key data science libraries including pandas, scikit-learn, and numpy.
Basic understanding of statistical and machine learning concepts, with emphasis on time-series methodologies.
Strong analytical skills combined with clear verbal and written communication abilities.
Collaborative attitude, self-driven, and proactive in seeking feedback and asking questions.

Preferred Qualifications

Academic or project experience related to the electricity sector, coupled with curiosity about relevant data and system dynamics.
Knowledge of integrating weather data for load and renewable energy forecasting.
Any familiarity with the Databricks platform.
Experience using Git/GitHub for version control and code management.

Term Details and Compensation

Term Duration: September to December 2026 (4 months).
Hourly Rate: $20 to $25, commensurate with study year, experience, and internal equity.
Work Schedule: 40 hours per week, 5 days on-site in Mississauga, Ontario.
Vacancy: Existing opportunity for Fall 2026 co-op placement.

Company Culture and Benefits

Engagements throughout the year including holiday celebrations, team dinners, social events such as bowling, go-karting, summer BBQs, and golf tournaments.
Opportunities for continuous learning through lunch-and-learns, challenges, and educational funding programs.
Active employee involvement in community support initiatives including food drives and fundraising via the Employee Initiatives Committee.

Hiring Process and Accessibility

Candidates will undergo a background check including criminal record and credential verification. Professional references will be requested.
Shortlisted applicants may be required to complete a practical assignment demonstrating problem-solving and analytical abilities.
The company is committed to accessibility and inclusive recruitment in compliance with relevant legislation. Accommodations are available on request throughout hiring and employment.

Data Science Co-op Student

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