The Team

Analytics sits within Jobber's Strategy & Analytics department, Jobber's internal consulting team and decision-support mechanism that connects data and business insight with the rest of the organization. Analytics is a central function that exists to drive business outcomes across Jobber's ecosystem.

The Role

Jobber is looking for a Manager, Customer Analytics (Sales & Marketing) to lead the analytics function supporting our Marketing & Channels and Sales & Partnerships pods. Reporting to the Senior Manager, Customer Analytics, this leader will manage a team of analysts and partner closely with Directors, Senior Directors, and VPs across Demand Generation, Brand Marketing & Communications, Sales, Partnerships, MarketingOps, SalesOps, and Finance.

In this role, you will set the technical, methodological, and strategic direction for high-impact Sales and Marketing analytics. You will own the measurement infrastructure that helps Jobber connect acquisition investment to subscription revenue growth, understand marketing effectiveness, evaluate channel and partnership performance, and improve visibility into CAC, LTV, payback, sales efficiency, revenue funnel performance, and go-to-market ROI.

This role requires a leader who combines strong people leadership, hands-on technical depth, and deep Sales and Marketing domain expertise. You will build trusted relationships with senior leaders, raise the bar for analytical quality, and develop analysts who can translate rigorous measurement into better growth decisions.

You will also help Jobber advance Analytics 2.0 in practice by using self-serve analytics, automation, responsible AI, and agentic workflows to scale trusted decision support and create more capacity for strategic, high-judgment analytical work.

What You'll Own

1. Team Leadership & Analytics Operating Model

• Hire, onboard, lead, coach, and develop a high-performing team of analysts supporting Demand Generation, Brand Marketing & Communications, Sales, and Partnerships, setting clear expectations and building the team's capabilities as Jobber's Sales and Marketing analytics needs scale.
• Establish a clear engagement and prioritization model for Sales and Marketing Analytics, creating scalable operating rhythms that balance strategic analysis, recurring reporting, cross-functional initiatives, self-serve enablement, and ad hoc stakeholder needs.
• Build a culture of analytical excellence, high accountability, curiosity, strong QA, documentation, peer review, business ownership, and continuous improvement.
• Partner with Analytics Engineering, BI, Data Science, Data Engineering, MarketingOps, and SalesOps to strengthen the data foundation, metric definitions, reporting infrastructure, and governed datasets that support Sales and Marketing decision-making.

2. Sales & Marketing Analytics Strategy

• Lead the analytics roadmap across Jobber's Marketing & Channels and Sales & Partnerships pods, ensuring the team is focused on the highest-impact opportunities across customer acquisition, demand generation, sales productivity, channel performance, partnership growth, and revenue efficiency.
• Partner with Sales and Marketing leadership to define success metrics, identify growth opportunities, evaluate strategic bets, and translate ambiguous business questions into clear analytical approaches and actionable recommendations.
• Help Jobber understand not just what is happening across the go-to-market funnel, but why it is happening, what it means, and what leaders should do next.

3. Performance Marketing, Demand Generation & Channel Measurement

• Define and evolve Jobber's marketing measurement framework across Marketing Mix Modelling (MMM), Multi-Touch Attribution (MTA), incrementality, experimentation, and forecasting, ensuring these methods work together as a unified system for decision-making rather than as siloed tools.
• Lead the design and operationalization of advanced marketing measurement approaches, including MMM, MTA, incrementality testing, spend efficiency curves, saturation analysis, and diminishing returns modelling, connecting marketing and channel investment to subscription revenue, CAC, payback, LTV, pipeline quality, and long-term customer value.
• Set standards for how analysts select, build, quality-assure, and interpret advanced measurement methods, including when to use MMM, MTA, incrementality testing, causal inference, forecasting, or simpler diagnostic approaches.
• Partner with Performance Marketing, Demand Generation, Brand Marketing & Communications, Partnerships, Finance, and MarketingOps to evaluate spend efficiency, channel mix, conversion quality, saturation, diminishing returns, and budget allocation trade-offs, including scenario analysis ahead of planning cycles.

4. Sales, Partnerships & Revenue Funnel Analytics

• Lead analytics that help Sales and Partnerships leaders understand funnel health, lead quality, conversion performance, rep and team productivity, pipeline creation, sales-assisted revenue, partner/referral performance, and opportunities to improve go-to-market efficiency.
• Build frameworks, dashboards, models, and decision-support tools that help leaders monitor performance, diagnose issues, and make better planning, resourcing, and prioritization decisions.
• Connect sales and marketing performance into a unified view of acquisition economics, helping Jobber understand how demand, channel mix, sales motion, and customer quality translate into durable revenue growth.

5. Executive Influence & Storytelling

• Bring an analytical perspective to growth strategy, planning, investment decisions, and operating reviews with Directors, Senior Directors, VPs, and cross-functional leaders.
• Translate complex analytical work into clear narratives, trade-offs, and recommendations that senior leaders can act on.

6. Analytics 2.0 & AI-Powered Decision Support

• Contribute to Jobber's Analytics 2.0 roadmap by identifying where AI, ML, automation, and agentic analytics can accelerate Sales and Marketing measurement, forecasting, diagnostics, storytelling, and self-serve decision support.
• Partner with Analytics Engineering, BI, Data Science, and Data Engineering to operationalize AI-assisted workflows and analytics agents for anomaly detection, campaign diagnostics, forecasting, attribution, causal inference, narrative generation, documentation, and QA.
• Champion governed self-serve analytics and trusted metrics so Sales and Marketing leaders can answer recurring performance questions without routing every request through an analyst, while preserving analytical quality and clear ownership.
• Help analysts adopt AI responsibly, validating outputs, understanding limitations, documenting methods, and using automation to create more capacity for strategic modelling and business influence.

What You Bring

Sales & Marketing Analytics Expertise

• Deep experience in Sales, Marketing, Growth, Revenue, Demand Generation, Performance Marketing, Channels, Partnerships, or GTM analytics, ideally in a high-growth SaaS or subscription business.
• Strong understanding of customer acquisition economics, including CAC, LTV, payback period, funnel conversion, pipeline quality, channel performance, sales efficiency, partner/referral performance, and subscription revenue growth.
• Deep, hands-on experience with marketing and GTM measurement approaches, including attribution, incrementality testing, experimentation, forecasting, budget allocation, and the practical limitations of each method.
• Experience helping senior Sales and Marketing leaders define success metrics, evaluate performance, diagnose growth opportunities, and make better decisions across the go-to-market funnel.
• Familiarity with marketing, sales, CRM, ad platform, lifecycle, partnerships, and revenue funnel data, including paid search, paid social, organic, referral, brand, partnerships, lifecycle marketing, and platform-specific measurement constraints from tools such as Google Ads, Meta, and programmatic ad platforms.
• Hands-on experience building or significantly contributing to advanced marketing measurement approaches such as Marketing Mix Modelling, Multi-Touch Attribution, incrementality experiments, geo or matched-market tests, synthetic control, spend efficiency curves, or causal inference methods, with the judgment to evaluate, challenge, and improve vendor or platform-reported outputs.

Technical & Methodological Skills

• Expert-level SQL skills, with the ability to work across complex data structures, build analytical datasets, and review analytical logic with confidence.
• Strong hands-on analytical skills, including performance measurement, exploratory analysis, cohort analysis, impact evaluation, experimentation, forecasting, scenario analysis, segmentation, predictive modelling, and causal inference techniques such as difference-in-differences, synthetic control, propensity score matching, or regression discontinuity.
• Strong proficiency in Python or R for modelling, automation, statistical analysis, and productionized analytics workflows; experience with MMM libraries or statistical modelling frameworks such as Robyn, Meridian, PyMC-Marketing, Bayesian modelling frameworks, or equivalent tools is a strong asset.
• Strong statistical judgment, including comfort with confidence intervals, effect size estimation, variance, seasonality, bias, model uncertainty, and balancing analytical rigour with pragmatic business decision-making.
• Experience with modern data stacks and BI tools such as dbt, Snowflake, Redshift, Looker, Tableau, or similar platforms, with a strong ability to build scalable, trusted reporting and decision-support assets.

Business & Leadership Skills

• Proven experience as a people leader in analytics, with a strong track record of developing, coaching, and empowering high-performing analysts.
• Strong strategic judgment, with the ability to shape priorities, influence senior leaders, and connect analytical work to company-level growth outcomes.
• Experience owning an analytics roadmap in a fast-moving environment with competing stakeholder needs and high-impact business decisions.
• Excellent stakeholder management skills, with the ability to build trust, clarify ambiguous asks, manage trade-offs, and influence Directors, Senior Directors, VPs, and cross-functional leaders through data-backed recommendations.
• Exceptional communication and storytelling skills, with the ability to translate complex analysis, uncertainty, and trade-offs into clear executive-ready narratives.
• Demonstrated ability to lead AI-assisted analytics adoption across a team, including identifying high-value use cases, setting QA and governance expectations, validating outputs, improving documentation, accelerating analysis, and helping analysts use AI to deliver better decision support without compromising quality.

Who You Are

• You are a strategic analytics leader who can operate at multiple altitudes. You can zoom into technical details when needed, but you always connect the work back to business decisions and outcomes.
• You are a strong people leader who creates clarity, raises the bar, and helps analysts do the best work of their careers.
• You are proactive and resourceful. You do not wait to be handed perfectly formed questions; you identify the highest-value problems, frame the trade-offs, and guide stakeholders toward better decisions.
• You are deeply curious about Sales and Marketing performance. You want to understand what drives acquisition, conversion, channel effectiveness, sales efficiency, partnership growth, and long-term customer value.
• You hold a high bar for analytical quality and measurement rigour, while staying pragmatic about what is useful, deployable, and decision-relevant in a real business environment.
• You communicate with clarity and confidence, especially when explaining uncertainty, trade-offs, and imperfect evidence to senior stakeholders.
• You are comfortable making trade-offs visible. You know how to say yes to the highest-impact work while helping stakeholders understand what must be deprioritized.
• You are excited by Analytics 2.0. You see emerging tools and operating models as ways to redesign how analytics teams deliver trusted, scalable decision support, not just as productivity shortcuts.

Location

We believe great collaboration is intentional, and sometimes that means coming together in person to build, brainstorm, and connect. To support this, the role is open to candidates based in one of our hub cities: Edmonton, Toronto, Vancouver, or Kitchener-Waterloo.

Compensation

At Jobber, we believe that compensation should be transparent, fair, and reflective of your experience and growth. This role has a minimum annu