The Staff Data Analyst - Product will provide advanced analytical support to the product team, leveraging data to optimize product development, improve user experiences, and drive business outcomes. You will manage product data, conduct deep-dive analysis into user behaviour, and help shape product decisions through insights on product performance, customer satisfaction, and feature usage. This role will directly influence product strategies, feature prioritization, and customer retention efforts by turning data into actionable insights. In line with Hootsuite’s distributed workforce strategy, our flexible work arrangement allows for remote work or a hybrid model. This role is open to applicants located in Toronto, Vancouver or remote throughout Canada. In this role, you will report to the Senior Manager, Analytics.

WHO YOU ARE:

• Tenacious. You are determined to succeed, and you are motivated by the success of customers, colleagues and the community.
• Curious. You are always learning and seeking ways to make things better.
• Conscientious. You keep your promises, taking your commitments to others seriously, and you have strong integrity.
• Humble. You lead with humility and empathy, respecting and learning from the perspectives of others.
  In all we do, our six guiding principles light the way:
  Step Up: Show the world what it looks like to live and work by these guiding principles. #StepUp
  One Team: Make Hootsuite a place where everyone feels safe, welcome, valued, and empowered to do their best work without compromising who they are. #OneTeam #FreeToBeMe
  Customer Obsessed: Focus relentlessly on helping our customers succeed. #CustomerObsessed
  Go Fast, Be Agile: Widen our competitive advantage by committing to speed and simplicity over perfection and complexity. #GoFastBeAgile
  Play to Win: Commit to building an incredible, profitable company for our customers, our employees, and our stakeholders. #PlayToWin #NoExcuses
  Neighbours & Allies: Give back to our communities and be an ally. #SocialForGood #Allies
  Accommodations will be provided as requested by candidates taking part in all aspects of the selection process.
  

  LI-EM

• Lead Product Analytics Initiatives: Manage key cross-functional product analytics projects, tracking feature adoption, user engagement, and product performance. Utilize advanced statistical methods and data visualization tools (e.g., Power BI) to provide actionable insights that help refine product features and overall product strategy.
• Product Performance and KPI Analysis: Analyze product KPIs such as user retention, activation rates, churn, and lifetime value. Use predictive analytics and data modeling techniques to recommend improvements in product features and user experience to drive higher engagement and satisfaction.
• Collaborate on Product Attribution and Impact Analysis: Work with the product team to develop and refine models that measure the impact of product features on key outcomes, such as user retention, conversion, and revenue growth. Use multi-touch attribution models to measure how different product interactions affect overall product success.
• Customer Segmentation and Personalization for Product Experience: Leverage product usage data to segment users based on behavior, demographics, and product usage patterns. Use these insights to develop personalized experiences, targeted feature rollouts, and recommendations that increase product engagement and customer satisfaction.
• A/B Testing and Experimentation: Lead A/B testing and controlled experiments to assess the impact of new product features, UI changes, and other user experience improvements. Apply statistical analysis to evaluate test results and provide actionable recommendations to refine and optimize product offerings.
• Forecasting and Trend Analysis: Utilize statistical models and machine learning algorithms to forecast product trends, user behaviour, and feature adoption. Provide forward-looking insights that help the product team prioritize features and plan future product roadmaps effectively.
• Mentor Data Analysts within the team through hands-on coaching and training to elevate their skills and impact.