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Intern, Data Science
2 months ago
At CN, we are committed to our pursuit of excellence. We take pride in delivering work of the highest standard, continually innovating to shape the railroad of the future. As responsible railroaders, we make the right decisions every time, putting safety first, acting with unwavering integrity, and holding ourselves accountable for our actions. We believe in succeeding together—by fostering inclusivity and collaboration, we sustainably deliver exceptional results for our customers.
We welcome students aboard to join our team and play a valuable role in the engine that keeps the North American economy on track. Expect an exciting environment where you’ll be encouraged to learn, grow, and be recognized for your unique ideas and contributions. Work on pivotal projects with experienced collaborators who will encourage you to share your perspectives, and thrive in our close-knit, safety-focused culture. The careers we offer are meaningful because the work we do matters. Join us and get your career moving
**Canadian National Railway Company (CN) is looking for a highly motivated person to fulfill a full-time (40h/week) Intern, Data Science position in Montreal, QC from Jan - Apr 2025.**
The Intern, Data Science is responsible for assisting the Data Science and Artificial Intelligence (AI) team to improve its practice and deliver analytics solutions. The incumbent performs various practice-related activities including standards creation, patterns documentation, and techniques and technologies review. Additionally, the incumbent performs various project-related activities, including data mining, model training and validation, pipeline creation, and data visualization.
**Major Responsibilities**
- Perform data Extract, Transform, Load (ETL) with multi-source datasets in preparation for data analytics initiatives
- Identify, analyze, and interpret trends in complex data sets
- Use data science techniques to find data patterns, anomalies, and optimization opportunities
- Strive to find the best ways to visualize data and articulate results
- Build data and model pipelines following Data Operations (DataOps) and Machine Learning Operations (MLOps) practices
- Work in an agile environment including regular meetings, Scrum, and Kanban
**Requirements**:
- Excellent communication skills (both verbal and written)
- Must be a critical thinker and fast learner
- Ability to analyze, model and interpret data
- Accuracy and attention to detail
- Ability to plan, prioritize and manage time
- Knowledge of databases (e.g., Structured Query Language (SQL), NoSQL, Graph, Search, Time-Series)
- Knowledge of business intelligence (e.g., Online Analytical Processing (OLAP), cubes, Power BI, Tableau)
- Knowledge of data design, engineering, and governance (e.g., ETL, Azure Data Factory, Databricks)
- Knowledge of DataOps, MLOps and Development Operations (DevOps) (Databricks, Azure ML, MLflow)
- Knowledge of programming languages SQL, Python, R, Scala, and Machine Learning (ML) frameworks and libraries (e.g., TensorFlow, PyTorch, Pandas, Numpy, Scipy).
- Knowledge of Microsoft Office (Excel, Access)
- Knowledge of Tableau and Python*
**Education**
Working towards a Bachelor’s Degree in Business, Industrial Engineering, Operations Research, Business Analytics, or Information Technology
- Any experience/education/skills/knowledge for these above would be considered as an asset
About CN
CN is a premium railroad that sustainably generates value for our customers, shareholders, employees, and stakeholders with an unwavering commitment to safety and service. Essential to the economy, to the customers, and to the communities it serves, CN safely transports more than 300 million tons of natural resources, manufactured products, and finished goods throughout North America every year. CN's network connects Canada’s Eastern and Western coasts with the U.S. South through an 18,800-mile rail network. CN and its affiliates have been contributing to community prosperity and sustainable trade since 1919. CN powers the North American economy and is committed to programs supporting social responsibility and environmental stewardship.