Customer Analytics Manager

Are you passionate about using data to drive impactful product decisions?

We’re looking for a Customer Analytics Manager to be part of our Business Analytics team.

The team:

Business Analytics is part of the Business Operations team,  our internal consulting team - they’re the decision support mechanism that connects data, business insights and an internal tech stack (systems) with the rest of the organization. In essence, Business Analytics is a central function that exists to drive business outcomes in all corners of Jobber’s ecosystem.

The role: 

Reporting to the Head of Customer Analytics, the Customer Analytics Manager will champion monetization (upsell / cross-sell) and retention analytics designed to profitably grow Jobber subscription revenue. 

The Customer Analytics Manager will:

• Be a thought partner to the stakeholder teams by proactively proposing analytical solutions and data insights that help improve customer engagement, grow customer lifetime value through upsell / cross-sell , increase retention and optimize sales & marketing ROI
• Collaborate with stakeholders to understand their business objectives, translate business objectives into proposed solutions (e.g. analysis, KPIs, BI, Data Science)) and socialize the proposals to ensure stakeholder’ alignment & buy-in
• Perform in depth (hands-on) analysis to drive insights, and inform business recommendations 
• Provide BI & Data team with requirements for customer analytics data, reports and dashboards
• Collaborate with Data Science team on ML / AI developments supporting Customer Analytics, GTM Marketing strategy and development of automated A/B testing capabilities
• Support experimentation initiatives by providing requirements for A/B design and executing success measurement and statistical quantification 

To be successful, you should have:

• Deep, hands-on experience creating and delivering custom analytics for SaaS product development
• Expert-level SQL programming skills 
• Solid understanding of complex relational data structures
• Data Science experience and Python are an asset 
• Experience in designing & productionalizing user-friendly product usage data is an asset
• Strong business acumen, strategic thinking, ability to see how the big picture and weigh pros and cons of different options
• Analytical creativity and flexibility
• Ability to design solutions under data & time constraints
  
• Experience of mentoring junior analysts in the team is an advantage

You should also:

• Be proactive and relentless. You are comfortable seeking information independently, solving conceptual problems, corralling resources and delivering results.
• To have a strong and confident communication style. You have the ability to actively listen, empathize and consult with stakeholders, and you can take something complex and difficult and make it easy to digest.
• Be comfortable in an ambiguous and fast-paced environment. We’re growing fast and things are changing every day - what worked yesterday might not anymore.