Data-Driven Merchandising Analyst

Couche-Tard

City of Moncton

Vor Ort

CAD 55.000 - 75.000

Vollzeit

Vor 2 Tagen
Sei unter den ersten Bewerbenden

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Zusammenfassung

Couche-Tard is seeking a data analytics professional to drive data-driven decision making across merchandising. You will analyze performance at multiple levels—department, cluster, vendor, item, and location—and support BU decisions on pricing, promotions, and assortment.

Ideal candidate has 2+ years of data analysis experience, strong Excel/PowerBI/Tableau skills, and effective communication abilities to translate complex findings for non-analytical peers.

Qualifikationen

  • Bachelor's degree required in Mathematics, CS, Engineering, Statistics, Business Analytics or related field.
  • 2+ years of work experience in data analysis or analytics.
  • Strong communication and writing skills.
  • Proficiency with Excel, Access and data visualization tools (PowerBI/Tableau).
  • Experience using SQL is a plus.

Aufgaben

  • Analyze merchandise performance at department, cluster, vendor, item and location levels.
  • Assess pricing, promotion, and assortment metrics across stores and regions.
  • Support BU pricing, promotions, and assortment decisions with data-driven insights.
  • Create visualizations and reports to communicate findings to non-technical audiences.
  • Collaborate with cross-functional teams to improve data-driven tools and processes.

Ausbildung

Bachelor's degree in Mathematics, Computer Science, Engineering, Statistics, Business Analytics or a related subject area

Tools

PowerBI
Tableau
Excel
Access
SQL

Jobbeschreibung

Couche-Tard is seeking a data analytics professional to drive data-driven decision making across merchandising. You will analyze performance at multiple levels—department, cluster, vendor, item, and location—and support BU decisions on pricing, promotions, and assortment.

Ideal candidate has 2+ years of data analysis experience, strong Excel/PowerBI/Tableau skills, and effective communication abilities to translate complex findings for non-analytical peers.

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