Data Science - Co-op Student
About The Position
Rodan Energy is a leading North American energy services company focused on Making Sustainable, Attainable. They provide innovative energy solutions to help clients reduce energy costs and GHG emissions, support electrification, and enhance grid efficiency. This co-op role offers hands-on experience in building forecasting models, exposure to time-series modeling, ML pipelines, and the Databricks platform in a production environment. The student will work alongside experienced data scientists and energy-market domain experts, gaining technical skills in a collaborative, high-impact setting. The role emphasizes in-office collaboration for hands-on learning and mentorship.
Requirements
- Currently enrolled in a registered Co-op program and working towards an undergraduate or graduate degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.
- Working knowledge of Python, SQL, Excel, and core data science libraries (e.g., pandas, scikit-learn, numpy).
- Foundational understanding of statistical or machine learning modeling concepts, ideally including time-series methods.
- Strong analytical thinking and clear written and verbal communication skills.
- Collaborative mindset, self-motivated, and comfortable asking questions and iterating on feedback.
Nice To Haves
- Coursework, projects, or work experience related to the electricity sector and curiosity about the data and dynamics that drive it.
- Familiarity with weather data integration for load and renewable forecasting.
- Any exposure to the Databricks platform.
- Familiarity with Git/GitHub for organizing and version-controlling your code.
Responsibilities
- Design, build, and validate time-series forecasting models for facility load, market demand, and electricity price signals.
- Explore and tune modeling approaches (statistical, ML, and deep learning) with guidance from the team, based on the forecasting horizon, data availability, and accuracy requirements.
- Contribute to ML pipelines on the Databricks platform using PySpark, MLflow, and Delta Lake.
- Build dashboards and automated reports in Databricks to replace manual Excel workflows.
- Learn from energy-market domain experts and incorporate their knowledge of market structures, tariff rules, and grid dynamics into model features and evaluation frameworks.
- Communicate model performance, assumptions, and limitations to both technical and non-technical stakeholders.
Benefits
- Lunch and learns
- Crossword challenges
- Education-funding programs
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What This Job Offers
Career Level
Intern
Education Level
Associate degree
