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Data Analyst Co-Op Student

Job in Vancouver, BC, Canada
Listing for: Lever, Inc.
Full Time, Apprenticeship/Internship position
Listed on 2026-09-30
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Business Systems & Technology Analysis, Data Engineering
Salary/Wage Range or Industry Benchmark: 42100 - 55100 CAD Yearly CAD 42100.00 55100.00 YEAR
Job Description & How to Apply Below
Position: People Data Analyst Co-Op Student

Department: People & Culture

Reports to: Senior Data Analyst, People Analytics

Location: North Vancouver, BC - This role is primarily based out of our North Vancouver office, and is open to hybrid remote work

Work Arrangement: Flexible, between in-office and home

Pay Range:$42,100 - $55,100; pay is dependent on year of study and related experience

Duration: Eight (8) months, Jan 4th, 2027 – August 13th, 2027

Hours Per Week: 40 hours per week, M-F

Your Co-Op Opportunity at ARC’TERYX:

As a People Data Analyst Co-op Student, you will join the Global People Analytics team to help transform people data into meaningful insights, clear stories, and practical intelligence for People & Culture partners. You will support exploratory analysis, data science opportunities, statistical analysis, and insight storytelling that helps teams better understand the employee experience and make more informed decisions with tools like Power BI, SQL, Python and Databricks.

This is an exciting opportunity to learn howpeopleanalytics, people science, data storytelling, automation, and emerging AI tools come together in a fast-moving, purpose-driven organization.

Meet Your Future Team:

The Global People Operations team provides Total Rewards, People Systems and People Analytics, Automation, and AI services. We play a critical role in scaling the People and Culture function and enabling the business. We partner across all areas to evolvepeoplepractices andmaintainstrong alignment with the needs of our growing, global organization.

If you were a People Data Analyst Co-Op Student now, here are some of the core activities you would be doing:
  • Applying statistical methods and data science techniques to explore workforce data, identify trends, patterns, outliers, and relationships.
  • Contributing to advanced analytical use cases, such as predictive modeling, segmentation, correlation analysis, and early hypothesis testing to explore emerging workforce questions.
  • Experimenting with AI and automation tools to make analytics discovery faster, clearer, and more engaging.
  • Translating data findings into clear, compelling visual stories that make workforce insights accessible.
  • Assisting with research design and insight development, including framing questions, reviewing relevant context, testing hypotheses, and translating findings into practical recommendations.
  • Learning how to work responsibly with workforce data, including privacy, fairness, quality, and trust.
Here are some of the things you will learn by the end of your Co-Op placement:
  • You will gain hands-on experience building end-to-end data pipelines and a predictive machine learning model using industry-leading cloud technologies including Azure, Databricks, and Power BI.
  • You will develop a strong understanding of how people analytics drives strategic workforce decisions, from automating data processes to delivering executive-level insights that influence how an organization attracts, retains, and develops its people.
  • You will leave with practical experience across the full analytics lifecycle. From raw data ingestion and modelling to stakeholder-facing dashboards and recommendations, all within a large-scale HR systems transformation.
Are you our next People Data Analyst Co-Op Student?
  • You are currently enrolled in a co-op eligible program in data science, statistics, business analytics, computer science, psychology, economics, HR, or a related field.
  • You are curious about people, data, and the stories hidden inside numbers and patterns.
  • You are comfortable applying statistical methods and data science techniques to predict outcomes, detect patterns, and translate findings into clear, actionable recommendations for business stakeholders.
  • You have some experience with statistics, Excel, Power…
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