Senior Customer Analytics Manager driving impactful business decisions through data analysis at Jobber. Partnering with cross-functional teams to enhance customer understanding and optimize business performance.
Responsibilities
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.
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.
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.
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 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.
Requirements
Expert-level SQL skills, with the ability to work efficiently across complex relational data structures and validate analytical logic with confidence.
Strong experience in B2B SaaS, marketplace, fintech, revenue, growth, product, customer, or go-to-market analytics.
A deep understanding of SaaS business models and customer journey metrics, such as funnel performance, conversion, activation, engagement, retention, expansion, monetization, customer quality, and customer value.
Proficiency with BI and data visualization tools such as Tableau, with a focus on clear, compelling, and actionable reporting and narratives.
Demonstrated experience with foundational and advanced analytics techniques, including performance measurement, exploratory analysis, impact evaluation, experimentation, forecasting, scenario analysis, simulation modelling, and predictive analytics.
Strong business acumen and strategic judgment, with the ability to connect analytical work to company-level growth, efficiency, and customer outcomes.
Excellent stakeholder management skills, with the ability to build trust, clarify ambiguous asks, influence priorities, and guide leaders toward better decisions.
A passion for storytelling through data, with the ability to distill complex analyses into simple, influential insights.
Practical fluency with AI-assisted analytics workflows, with the judgment to use AI responsibly, validate outputs, and own the quality of the final work.
Intellectual curiosity, creativity, and adaptability in solving open-ended business problems in a fast-moving environment.
Demonstrated ability to mentor analysts, lead through influence, and operate as a senior individual contributor owning one or more business domains.
Proven ability to thrive under pressure, navigate ambiguity, and bring structure to complex or competing demands.
Experience with Python, dbt, Snowflake, Salesforce or other CRM/customer systems, data modelling, and productionized analytics workflows is a strong asset.
Benefits
equity rewards
annual stipends for health and wellness
retirement savings matching
extended health package with fully paid premiums for body and mind
dedicated talent development program including career coaching and opportunities for career development
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