Data Science Student

PCL Construction

Data Science Student supporting PCL Construction’s infrastructure projects through exploratory analysis, machine learning, and visualizations. Building a portfolio-focused capstone prototype under data science supervision.

Posted 9/7/2026full-timeEdmonton • 🇨🇦 CanadaEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in exploratory data analysis, machine learning modeling, and data visualization using industry-leading tools. Strong analytical skills with a solid foundation in statistics and experience in programming environments such as Python and R.

Highest-signal resume keywords

Exploratory Data AnalysisMachine Learning ModelingData VisualizationStatistical ProgrammingAnalytical Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnnotationBenchmarking TechniquesRegression ModelsClustering ApproachesApplied StatisticsProbability

Soft Skills

Excellent Oral CommunicationExcellent Written Communication

Tools & Technologies

Python Scientific StackRPowerBIData Pipeline Tools

Industry Keywords

Data ScienceQuantitative FieldLarge DatasetsCapstone Project

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Gain proficiency in and perform exploratory data analysis and present insights
Prepare datasets for visualization and machine learning modeling
Train machine learning systems using data annotation and benchmarking techniques
Assess AI/ML model performance and propose improvements with colleagues
Prepare data visualizations using industry-leading tools for stakeholders
Document results, successes, and lessons learned
Develop a capstone project proposal contingent on successful early work
Engage with relevant people to inform the capstone work
Build a prototype or visualization
Assess and present capstone results
Work under the direct supervision of the Manager, Data Science

Requirements

What you’ll need

Currently enrolled in a postsecondary program
Outstanding bachelor's or mathematics student in engineering, computing, or mathematical sciences, or pursuing an MSc in a quantitative field
Analytical skills demonstrated through coursework, projects, or research involving analysis of large datasets
Coursework in statistics, particularly applied statistics and probability
Ability to discuss regression models and clustering approaches
Prior exposure to a statistical or scientific programming environment is helpful
Familiarity with or willingness to learn Python scientific stack, R, PowerBI, and data pipeline tools
Excellent oral and written communication skills
Availability for a 4-, 8-, or 12-month term starting in January 2027

Benefits

Comp & perks

Challenging work assignments
Supportive work environment
Personal and professional growth opportunities
Opportunity to build a portfolio through a capstone project
Support and guidance for developing a proposal, engaging stakeholders, building a prototype or visualization, and presenting results
Employee-owned company environment
Accommodation support during the application process