Senior Data Scientist, Data Valorization
@ Desjardins

Montreal, Quebec, Canada
CA$120,000
On Site
Posted 24 days ago

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XXXXXXXXXX XXXXXXXXXXX XXXXXXXXXX******* @desjardins.com
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Job Details

Overview

The Senior Data Scientist, Data Valorization at Desjardins transforms data into value-added insights to drive business decisions. This role is key in advising teams and leadership on leveraging data, developing analytical solutions, and operationalizing changes in large-scale cross-sector projects.

Key Responsibilities

  • Simplify complex data concepts for decision-making bodies.
  • Identify and evaluate strategic data opportunities aligned with business priorities.
  • Define solutions and create an analytical roadmap integrated with business plans.
  • Align delivery teams in designing and developing complex analytical solutions.
  • Advise business sectors on integrating data solutions into operations.
  • Establish performance metrics and advise on solution deployment.
  • Coach senior management and decision-making bodies on data strategy.

What We Offer

Competitive salary, annual bonus, flexible vacation, defined benefit pension plan, group insurance, health and wellness reimbursements, and telework equipment. Eligibility criteria apply.

Qualifications

Bachelor's degree in a related field with a minimum of eight years of relevant experience. French language proficiency is required.

Key skills/competency

  • data transformation
  • analytical solutions
  • strategic initiatives
  • leadership
  • cross-sector collaboration
  • data roadmap
  • performance measurement
  • coaching
  • stakeholder management
  • French proficiency
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How to Get Hired at Desjardins

🎯 Tips for Getting Hired

  • Research Desjardins culture: Understand their mission and core values.
  • Customize your resume: Highlight analytical and leadership skills.
  • Showcase projects: Detail cross-sector data initiatives clearly.
  • Prepare for interviews: Practice strategic and technical questions.

📝 Interview Preparation Advice

Technical Preparation

Review advanced statistical modeling techniques.
Practice data visualization tool usage.
Study analytical roadmap development methods.
Familiarize with performance metric systems.

Behavioral Questions

Describe a leadership experience with data projects.
Explain handling cross-functional team challenges.
Discuss decision-making under data uncertainty.
Share experience coaching senior professionals.

Frequently Asked Questions