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Data Science - Co-op Student (Winter 2027)

  • Mississauga, ON, Canada

Internship

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Job details

Job type
Internship
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Posting language
English
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Original job description

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, helping shape the future of energy management. 

  • Product Market Fit: With a 98% client retention rate and consistent year-over-year 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, innovation, and sustainability.
     

What Makes This Role Great:

  • Gain hands-on experience building forecasting models that inform real facility, market, and pricing decisions
  • Exposure to time-series modeling, ML pipelines, and the Databricks platform in a live production environment
  • Work alongside experienced data scientists and energy-market domain experts
  • Opportunity to build technical skills in a collaborative, high-impact environment
  • In-office collaboration, five days a week, designed for hands-on learning and mentorship

Key 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 (we’ll teach you the platform)
  • 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
Required Skills & Qualifications
  • 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 Have:
  • 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
Term Details, Compensation & Work Location
  • Term: January 2027 – April 2027 (4-month co-op term)
  • Compensation: $20.00 - $25.00 per hour, based on year of study, relevant experience, and internal equity
  • Schedule: 40-hour work week
  • Location: Mississauga, ON
  • Work Arrangement: 5 days per week in-office
  • Vacancy Status: This posting is for an existing Winter 2027 co-op opportunity
     
Life at Rodan – Our Culture:
At Rodan, we believe a great workplace goes beyond the work itself. Recognized as Canada’s Top Small & Medium Employer of 2026, we’ve built a culture rooted in collaboration, celebration, and giving back. Here’s what you can look forward to when you join the team:
  • 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.
     

Apply Now: If you're a curious, driven student who's passionate about data, modeling, and the future of energy, we want to hear from you! Please submit your resume, cover letter, and unofficial transcript together as one attachment.

Hiring Process
Rodan Energy's hiring process is designed to identify candidates who are the right fit - technically, culturally, and professionally. As part of our process, candidates should be aware of the following:

  • 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 and credential verification. Professional references will also be collected as part of the process
  • Assignment: Shortlisted candidates may be asked to complete a practical assignment. This is an opportunity to demonstrate your problem solving approach, creativity, and how you think through a real-world dataset

We respect your time and will provide clear instructions and reasonable timelines for any assignments requested.

Artificial Intelligence: Rodan Energy Solutions uses artificial intelligence-enabled tools to support the screening and/or assessment of applicants during the recruitment process. All hiring decisions are reviewed by members of our hiring team.

Rodan Energy Solutions is committed to inclusive, accessible recruitment and employment experience in compliance with the Accessibility for Ontarians with Disabilities Act, 2005 (AODA). Accommodations are available upon request throughout the hiring process and, if hired, during employment. If you require an accommodation, please contact Asmin.Shadir@rodanenergy.com so we can work with you to meet your needs in a manner that respects dignity, independence, integration, and equal opportunity.

More about this job

Responsibilities

Build and validate time-series forecasting models for facility load, market demand, and electricity prices, and contribute to production machine-learning pipelines on Databricks. Create dashboards and automated reports, incorporate energy-market knowledge into model features and evaluation, and communicate model performance and limitations to stakeholders.

Requirements

Applicants must be enrolled in a registered co-op program and pursuing an undergraduate or graduate degree in data science, statistics, computer science, engineering, or a related quantitative field. They should have working knowledge of Python, SQL, Excel, and core data science libraries, foundational modeling knowledge, strong analytical and communication skills, and a collaborative, self-motivated approach.

Skills

  • Python
  • SQL
  • Excel
  • Pandas
  • Scikit-Learn
  • NumPy
  • Time-Series Forecasting
  • Statistical Modeling
  • Machine Learning
  • Deep Learning
  • PySpark
  • MLflow
  • Delta Lake
  • Databricks
  • Git
  • Data Visualization

Benefits

  • Education Funding Programs
  • Team Events

Visa sponsorship

Not detected in the job text

Hiring contact email

Asmin.Shadir@rodanenergy.com

Categories

  • Data & Analytics
  • Energy
  • Technology
  • Science & Research
  • Environmental & Sustainability

Keywords

  • Data Science
  • Energy Management
  • Electricity Markets
  • Time-Series Forecasting
  • Facility Load Forecasting
  • Market Demand Forecasting
  • Electricity Price Forecasting
  • Statistical Modeling
  • Machine Learning
  • Deep Learning
  • Python
  • SQL
  • Excel
  • Pandas
  • Scikit-Learn
  • NumPy
  • Databricks
  • PySpark
  • MLflow
  • Delta Lake
  • Machine-Learning Pipelines
  • Dashboard Development
  • Automated Reporting
  • Weather Data Integration
  • Renewable Forecasting
  • Git
  • GitHub
  • Tariff Rules
  • Grid Dynamics
  • Energy Sustainability

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