Data Analyst

TL;DR

Data Analyst: Identifying, analyzing, and interpreting customer experience data to provide actionable insights for North American brands with an accent on reporting, presentation, and cross-functional collaboration. Focus on delivering high-quality data strategies, performing complex data wrangling, and leveraging BI tools to drive business outcomes.

Location: Must be based in or able to commute to Kanata, Ontario (Hybrid)

Salary: $60,000–$70,000 per year

Company

hirify.global provides top brands with actionable customer experience insights through a comprehensive reporting platform and operational audits.

What you will do

• Identify, analyze, and interpret data trends to provide actionable client insights.
• Plan and create professional reports and presentations for internal and external stakeholders.
• Collaborate with Customer Success and Sales teams to communicate findings and strategy.
• Work with internal teams to define data delivery processes and tool requirements.
• Perform data cleansing, wrangling, and validation to ensure high-quality outputs.
• Support Marketing and Product teams on various research projects.

Requirements

• 2 years of relevant experience in a data analysis role.
• Strong proficiency in Excel and PowerPoint.
• Experience with BI tools, specifically Tableau.
• Solid understanding of statistical principles such as correlation and regression.
• Ability to generate business-relevant insights using both traditional methods and AI.
• Strong verbal and written communication skills in English.

Nice to have

• Experience in the CX industry or Marketing Studies.
• Proficiency in Python (Pandas, scikit-learn, JSON).
• French language skills.
• Data analysis or science-related certifications.

Culture & Benefits

• Opportunity to work with a passionate team focused on customer experience management.
• Exposure to diverse data sources including surveys, mystery shopping, and operational audits.
• Commitment to professional growth and development within a expanding business.
• Collaborative environment utilizing both traditional and modern technology stacks.