Manager, Data & Analytics

With a legacy spanning over a century, our client operates a diverse portfolio of retail banners, wholesale businesses, and production facilities, ensuring a high-quality and a commitment to excellence in customer service, innovation, and community support. Their dedication to these values is reflected in their industry-leading loyalty programs, proprietary brands, and ongoing efforts to enhance operational efficiencies.

They are currently seeking a Manager of Data & Analytics to leverage all aspects of data and analytics to drive large-scale projects and continuous improvement initiatives that guide decision-making and deliver high-quality insights. This role will also support the development and management of customer data and insights using one of the largest and most comprehensive data sets in Canada to support the loyalty programs, Marketing, Retail Operations and Merchandising.

This role offers a base salary (97-130k target), incentive plan, benefits, RRSP/pension plan, hybrid work structure.

Key Responsibilities:

• Leading and developing a team of data analysts
• Collaborating with multiple stakeholders to understand business questions, processes, and KPIs
• Managing the data and analytics support for key projects and initiatives
• Discovering unique and creative insights to identify new opportunities for driving business value
• Elevating and automating our statistical testing, offer attribution analysis, and customer segmentation
• Becoming an expert in the relevant datasets within your analytics domain

Key Qualifications:

• A degree in a STEM discipline
• Minimum 5 years of relevant experience in data analytics or data science
• Advanced Python coding skills
• Experience in other programming languages is a asset
• Advanced understanding of SQL
• Strong communication and story telling skills, with a high EQ
• Experience using experimental design principles such as A/B and multivariate testing and working with business stakeholders to formulate testable hypotheses
• Understanding of advanced analytics and data science methods such as anomaly detection, forecasting, and supervised and unsupervised learning
• Experience with visualization and reporting tools such as Power BI or Tableau
• Experience in cloud environments such as Azure, GCP, or AWS and big data tools such as Spark and Databricks