Lead, Data and Analytics at Vetster
Toronto, ON, Canada -
Full Time


Start Date

Immediate

Expiry Date

15 Apr, 25

Salary

0.0

Posted On

17 Jan, 25

Experience

0 year(s) or above

Remote Job

No

Telecommute

No

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description
Responsibilities

WHY YOU’LL LOVE THIS ROLE

  • Product Impact: Directly influence the development and success of our products by providing actionable insights.
  • Data-Empowered Culture: Play a key role in fostering a data-informed mindset across the organization.
  • Professional Growth: Opportunity to lead initiatives, collaborate with diverse teams, and shape your career path in product analytics.

YOUR RESPONSIBILITIES

  • Data Strategy & Team Leadership: Managing the Data team (reporting into the Director of Product), supporting the development of our data strategy, fostering team empowerment, and identifying scalable solutions to meet the evolving demands of a growing organization.
  • Product Analytics Leadership: Lead in-depth analyses of user behavior, cohorts, and customer journeys using tools like Fullstory, Amplitude, or Mixpanel. Identify and activate opportunities for product improvement to enhance user engagement and retention.
  • Analytics & Insights: Analyze product performance metrics to inform strategic decisions. Provide clear, actionable recommendations to stakeholders.
  • Experimentation & Testing: Plan, Design, execute, and analyze A/B tests and multivariate experiments to optimize product features and user experience.
  • Data Visualization & Storytelling: Create compelling reports and dashboards using tools like Tableau or Looker. Present insights in a clear and impactful manner to drive decision-making.
  • Cross-Functional Collaboration: Partner with product, engineering, marketing, and business teams to align analytics efforts with company goals. Advocate for data-driven decision-making across departments.
  • Event Data Oversight: Work closely with engineering teams to ensure accurate tracking of user interactions and events. Define data requirements and validate data integrity.
  • Continuous Improvement: Stay updated on industry trends in product analytics. Proactively suggest new tools, methodologies, or approaches to enhance analytics capabilities.
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