Who you are

• This is a high-leverage role for someone who can lead analysts, build trusted stakeholder relationships, and help evolve the team from reactive reporting toward scalable, AI-enabled decision support
• Proven experience as a people leader in analytics, with a strong track record of developing, coaching, and empowering high-performing analysts
• Deep expertise in Customer Success, post-sales, customer lifecycle, or SaaS business analytics, with hands-on experience analyzing onboarding, customer engagement, support performance, retention, churn, expansion, or account growth
• Strong business acumen and strategic judgment, with the ability to shape initiatives, influence priorities, and connect analytical work to company-level outcomes
• Expert-level SQL skills, with the ability to work efficiently across complex relational data structures and review analytical logic with confidence
• Proficiency with BI and data visualization tools, such as Tableau, with a focus on creating clear, compelling, and actionable reporting and narratives
• Demonstrated experience with foundational and advanced analytics techniques, including performance measurement, exploratory analysis, impact evaluation, scenario analysis, experimentation, simulation modelling, and predictive analytics
• Practical fluency with AI-assisted analytics workflows, with the ability to help analysts use AI responsibly, validate outputs, and own the quality of the work
• Strong stakeholder management skills, with the ability to build trust, clarify ambiguous asks, manage competing priorities, and influence leaders through data-backed recommendations
• A passion for storytelling through data, with exceptional communication skills and the ability to distill complex analyses into clear, influential insights
• A solid understanding of SaaS business models, customer health metrics, retention dynamics, expansion levers, and the operational drivers of long-term customer value
• Intellectual curiosity, creativity, and adaptability in solving open-ended business problems in a dynamic environment
• Proven ability to thrive under pressure, maintain focus amid ambiguity, and bring structure to complex or competing demands
• Experience with Python, dbt, data modelling, customer health scoring, lifecycle analytics, or productionized analytics workflows is a strong asset
• Be a strong people leader who creates clarity, raises the bar, and helps analysts do the best work of their careers
• Be proactive and resourceful, with a bias for action. You’re comfortable navigating ambiguity, solving conceptual problems, corralling resources, and delivering results
• Communicate with clarity and confidence. You actively listen, empathize with stakeholders, and translate complex concepts into simple, actionable insights
• Be comfortable making trade-offs visible. You know how to say yes to the highest-impact work while helping stakeholders understand what must be deprioritized
• Care deeply about quality. You value strong analytical foundations, thoughtful QA, documentation, peer review, and reproducible work
• Be excited about the future of analytics. You see AI and automation not just as productivity tools, but as opportunities to redesign how analytics teams deliver impact
• Thrive in a fast-paced and evolving environment. You adapt quickly, embrace change, and stay focused even when yesterday’s playbook no longer applies

What the job involves

• Then Jobber might be the place for you! We’re looking for a Manager, Customer Analytics (Post-Sales) to join our Analytics & Insights team
• Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology
• 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 Manager, Customer Analytics (Post-Sales) will lead a team of analysts responsible for driving insight and analytical impact across Jobber’s post-sales customer journey, including onboarding, support, account management, lifecycle engagement, retention, expansion, and customer value optimization
• Reporting to the Senior Manager, Customer Analytics, you’ll combine people leadership, strategic partnership, and strong analytical judgment to help Jobber deepen its understanding of what drives customer success and scale data-informed decision-making across the business
• You’ll help establish clear priorities, manage stakeholder demand, develop reusable analytics assets, and ensure the team’s work translates into measurable business impact
• You’ll lead initiatives that assess how customers onboard, engage, grow, renew, expand, and retain over time
• You’ll help identify opportunities to improve the customer experience, reduce churn and downgrade risk, increase expansion, and measure the impact of programs, policies, and interventions designed to help customers get more value from Jobber
• Lead and develop a high-performing team
• Lead, coach, and empower a team of analysts who deliver strategic insights and drive measurable business impact
• Build a collaborative, high-accountability team environment that values curiosity, analytical rigour, business impact, and continuous improvement
• Develop talent through mentorship, feedback, and coaching, helping analysts grow both their technical depth and strategic judgment
• Help the team prioritize work based on business impact, stakeholder needs, company priorities, and available capacity
• Model analytical leadership by helping the team translate ambiguous business questions into clear analytical approaches, actionable recommendations, and better decisions
• Partner with leaders across Customer Onboarding, Support, Account Management, Lifecycle Marketing, Product Marketing, and other cross-functional teams to define success metrics, evaluate initiatives, and uncover opportunities to improve customer outcomes
• Lead high-impact analyses on onboarding performance, customer engagement, support effectiveness, customer health, retention patterns, churn and downgrade risk, expansion opportunities, and long-term customer value
• Develop frameworks, models, dashboards, and decision-support tools that connect insights across the customer lifecycle and enable proactive management of customer health and growth
• Translate business outcomes into analytical roadmaps that balance immediate decision needs with scalable, forward-looking solutions
• Help leaders understand not just what happened, but why it happened, what it means, and what Jobber should do next
• Help establish a clear engagement model for Customer Analytics stakeholders, including how work is prioritized, scoped, routed, and delivered
• Balance functional stakeholder support, cross-functional initiatives, recurring reporting, migration work, enablement, and strategic analysis in a way that makes trade-offs visible and intentional
• Protect the team’s focus by distinguishing between must-do work, essential recurring needs, self-serve opportunities, and lower-priority ad hoc requests
• Identify recurring or repeatable analytics work that should become automated, standardized, documented, or moved into self-serve
• Partner with Analytics Engineering, BI, Data Science, and other Analytics & Insights teams to improve the data foundation, metric definitions, reporting infrastructure, and analytical workflows that support Customer Analytics
• Act as a strategic thought partner and internal consultant to customer-facing and cross-functional leaders, providing analytical perspectives that inform business strategy, operational priorities, and resource planning
• Anticipate business needs and proactively identify analytical opportunities that unlock growth, efficiency, retention, or customer experience improvements
• Frame complex business challenges into clear hypotheses, lead structured problem-solving, and deliver recommendations that influence decisions at multiple levels of the organization
• Champion experimentation, scenario modelling, impact evaluation, customer health measurement, and predictive analytics as tools for improving the quality of business decisions
• Bring strong judgment to analytical work, ensuring the team is focused on the decisions being made, not just the analyses being produced
• Promote strong analytics practices across the team, including clear metric design, QA, documentation, peer review, reproducible workflows, and thoughtful ownership of recurring assets
• Build compelling, executive-ready narratives that connect insight to action and create alignment around key opportunities
• Enable self-serve analytics and scalable reporting, empowering business partners to make confident, data-informed decisions
• Help the team adopt AI and automation responsibly, using emerging tools to accelerate analysis, reduce manual reporting, improve documentation, and shift analyst time toward higher-judgment work
• Encourage curiosity and innovation by continuously exploring new data sources, analytical techniques, AI-assisted workflows, and storytelling approaches that improve understanding of the customer experience