Forecasting Data Science Co-op — Energy Analytics

Rodan Energy Solutions Inc.; Mississauga; On-site; CAD 28,000 - 34,000; Full time

Benefits offered by this job

Mentorship

Hands-on learning

In-office five days a week

Job summary

Rodan Energy Solutions Inc. invites a data science co-op to design and validate time-series forecasting models for facility load and energy market signals. You will explore ML approaches, contribute to Databricks pipelines with PySpark, and build automated dashboards to streamline reporting.

You will work alongside energy-market domain experts in a hands-on, in-office setting, gaining practical experience while learning through mentorship and collaborative projects.

Qualifications

• Currently enrolled in a registered Co-op program pursuing an undergrad or grad degree in Data Science, Statistics, CS, Engineering or related quantitative field.
• Proficient in Python, SQL, Excel and core data science libraries (pandas, scikit-learn, numpy).
• Foundational understanding of statistical or ML modeling, ideally time-series methods.
• Strong analytical thinking and clear written and verbal communication skills.
• Collaborative mindset, self-motivated, comfortable with feedback and iteration.

Responsibilities

• Design, build, and validate time-series forecasting models for facility load and market signals.
• Explore and tune modeling approaches (statistical, ML, deep learning) with guidance based on horizon and data.
• Contribute to ML pipelines on Databricks using PySpark, MLflow, and Delta Lake.
• Build dashboards and automated reports in Databricks to replace Excel workflows.
• Incorporate market knowledge into feature engineering and evaluation frameworks.
• Communicate model performance, assumptions, and limitations to stakeholders.

Skills

Python

SQL

Excel

Pandas

Scikit-learn

Numpy

Time-series

Communication

Collaboration

Education

Data Science

Statistics

Computer Science

Engineering

Tools

Databricks

PySpark

MLflow

Delta Lake

Git/GitHub

Job description

Rodan Energy Solutions Inc. invites a data science co-op to design and validate time-series forecasting models for facility load and energy market signals. You will explore ML approaches, contribute to Databricks pipelines with PySpark, and build automated dashboards to streamline reporting.

You will work alongside energy-market domain experts in a hands-on, in-office setting, gaining practical experience while learning through mentorship and collaborative projects.