We’re looking for a Senior Customer Analytics Manager to be part of our Analytics team.
The Team:
Analytics is part of the Strategy & Analytics department, our internal consulting team - they’re the decision support mechanism that connects data & business insights with the rest of the organization. In essence, Analytics is a central function that exists to drive business outcomes in all corners of Jobber’s ecosystem.
The Role:
Reporting to the Senior Manager, Customer Analytics, the Senior Customer Analytics Manager will be a senior analytics partner for one or more of Jobber’s high-priority Customer Analytics domains.
This role will partner closely with business leaders and cross-functional teams to help Jobber better understand customer behaviour, business performance, growth opportunities, and the drivers of long-term customer value. Depending on business priorities, this work may span areas such as acquisition, onboarding, lifecycle engagement, product adoption, monetization, retention, expansion, customer success, or other strategic customer domains.
You will lead high-impact analytical work across the customer journey, including funnel performance, customer segmentation, conversion, engagement, product usage, retention, expansion, operational effectiveness, and long-term value.
This is an individual contributor leadership role, not a people leadership role. You will not directly manage a team, but you will be expected to lead through influence, own one or more important business domains, shape analytical roadmaps, mentor and guide analysts, manage senior stakeholder relationships, and ensure analytics work translates into better decisions.
The ideal candidate brings strong business acumen, deep analytical expertise, and excellent communication skills. They are comfortable turning ambiguous business questions into structured analytical approaches, building clear recommendations, and influencing decisions at multiple levels of the organization.
The Senior Customer Analytics Manager will:
Lead strategic customer analytics and insight
Act as a strategic thought partner and internal consultant to stakeholders across one or more high-priority Customer Analytics domains, helping them clarify business questions, evaluate opportunities, measure performance, and make better decisions.
Collaborate closely with teams across Jobber, including Revenue Operations, Strategy, Marketing Analytics, Product & Fintech Analytics, BI & Analytics Engineering, Data Science, and relevant go-to-market or customer-facing teams.
Lead deep-dive analyses across the customer journey, including acquisition, onboarding, engagement, product adoption, monetization, retention, expansion, customer quality, and long-term customer value.
Help define, refine, and govern the KPIs that matter most for the assigned domain or domains, including performance, efficiency, customer quality, customer outcomes, and downstream business impact.
Translate complex business questions into clear analytical plans, decision frameworks, and actionable recommendations.
Evaluate the impact of strategic initiatives, operational changes, go-to-market motions, customer programs, product or lifecycle initiatives, and other business priorities.
Help leaders understand not just what happened, but why it happened, what it means, and what Jobber should do next.
Support decision-making across assigned domains
Build a strong analytical understanding of the assigned domain or domains, including how different customer segments, behaviours, channels, products, teams, or motions contribute to business performance.
Identify opportunities to improve growth, efficiency, prioritization, customer experience, customer quality, and long-term value.
Support strategic planning, forecasting, target setting, business cases, and resource allocation decisions.
Partner with cross-functional teams and business leaders to improve reporting foundations, metric definitions, funnel or journey visibility, and decision-making workflows.
Analyze the quality and long-term value of different customer groups, helping Jobber optimize for durable growth rather than short-term volume alone.
Create reusable frameworks and decision tools that help teams evaluate trade-offs across growth, efficiency, customer outcomes, and operational complexity.
Drive experimentation, impact evaluation, and advanced analytics
Support experimentation and measurement strategies for strategic initiatives, including A/B tests, pilots, campaigns, lifecycle programs, product initiatives, operational changes, and customer-facing programs.
Apply advanced analytics techniques such as impact evaluation, scenario analysis, simulation modelling, forecasting, segmentation, and predictive analytics to inform strategic decisions.
Partner with Data Science on more complex modelling opportunities, such as customer scoring, prioritization, churn or expansion propensity, automation, AI-assisted workflows, or other predictive systems.
Bring strong judgment to ambiguous measurement problems, including cases where perfect experimentation is not possible and directional decision support is still needed.
Help stakeholders understand analytical confidence, limitations, trade-offs, and recommended next actions.
Build trusted stakeholder partnerships and executive-ready communication
Build trusted relationships with senior leaders and cross-functional stakeholders by understanding their goals, shaping analytical roadmaps, and proactively identifying opportunities.
Communicate insights through clear, compelling, executive-ready narratives that connect analysis to decisions and business outcomes.
Present findings, recommendations, dashboards, and decision frameworks in business reviews, leadership forums, and cross-functional meetings.
Make trade-offs visible when stakeholder demand exceeds capacity, helping teams prioritize the work that will have the greatest business impact.
Collaborate across Analytics & Insights to ensure Customer Analytics work connects cleanly with other analytics teams and pods, BI & Analytics Engineering, and Data Science.
Advance scalable analytics and AI-enabled workflows
Identify recurring or repeatable analytics work that should become automated, standardized, documented, or moved into self-serve.
Partner with BI & Analytics Engineering to improve the data foundation, semantic layer, reporting infrastructure, and self-serve capabilities that support Customer Analytics decision-making.
Use AI-assisted analytics workflows responsibly to accelerate exploration, coding, documentation, QA, and storytelling while maintaining strong ownership of output quality.
Promote high-quality analytics practices, including clear metric definitions, reproducible workflows, thoughtful QA, documentation, peer review, and data quality stewardship.
Build scalable assets, dashboards, models, and analytical frameworks that reduce manual reporting and shift analyst time toward higher-judgment work.
Ensure insights are timely, trusted, actionable, and connected to meaningful business outcomes.
Lead as a senior individual contributor, you will:
Lead one or more important Customer Analytics domains through influence, ownership, and strong judgment.
Provide mentorship, peer review, and analytical guidance to analysts working in or adjacent to those domains.
Raise the bar for analytical quality, stakeholder communication, and business impact across the Customer Analytics team.
Contribute to team-wide best practices around prioritiza