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Jobber

SaaS for home-service operations management

Manager Customer Analytics - Sales & Marketing

Data ScienceConfirmed live in the last 24 hours
Full-timeCA$139.4k - CA$229k /yr

About the Job

Requirements

  • Deep experience in Sales, Marketing, Growth, Revenue, Demand Generation, Performance Marketing, Channels, Partnerships, or go-to-market analytics, ideally in a high-growth software-as-a-service or subscription business.
  • Strong understanding of customer acquisition economics, including customer acquisition cost, lifetime value, payback period, funnel conversion, pipeline quality, channel performance, sales efficiency, partner/referral performance, and subscription revenue growth.
  • Deep, hands-on experience with marketing and go-to-market 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, customer relationship management, advertising 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 advertising platforms.
  • Hands-on experience building or significantly contributing to advanced marketing measurement approaches such as Marketing Mix Modelling, Multi-Touch Attribution, incrementality experiments, geographic 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.
  • Expert-level SQL skills, including working across complex data structures, building analytical datasets, and reviewing analytical logic.
  • 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.
  • 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 business intelligence tools such as dbt, Snowflake, Redshift, Looker, Tableau, or similar platforms, with the ability to build scalable, trusted reporting and decision-support assets.
  • Proven experience as a people leader in analytics, with a track record of developing, coaching, and empowering high-performing analysts.
  • Strong strategic judgment, including shaping priorities, influencing senior leaders, and connecting 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.
  • Stakeholder management skills, including building trust, clarifying ambiguous asks, managing trade-offs, and influencing Directors, Senior Directors, VPs, and cross-functional leaders through data-backed recommendations.
  • Communication and storytelling skills, including translating 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 quality assurance and governance expectations, validating outputs, improving documentation, accelerating analysis, and helping analysts use AI to deliver better decision support without compromising quality.

Responsibilities

  • Hire, onboard, lead, coach, and develop a high-performing team of analysts supporting Demand Generation, Brand Marketing & Communications, Sales, and Partnerships; set clear expectations and build team capabilities as analytics needs scale.
  • Establish an engagement and prioritization model for Sales and Marketing Analytics, creating scalable operating rhythms for strategic analysis, recurring reporting, cross-functional initiatives, self-serve enablement, and ad hoc stakeholder needs.
  • Build a culture of analytical excellence, accountability, curiosity, quality assurance, documentation, peer review, business ownership, and continuous improvement.
  • Partner with Analytics Engineering, business intelligence, Data Science, Data Engineering, Marketing Operations, and Sales Operations to strengthen the data foundation, metric definitions, reporting infrastructure, and governed datasets that support Sales and Marketing decisions.
  • Lead the analytics roadmap across Marketing & Channels and Sales & Partnerships, focusing the team on high-impact opportunities in 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 analytical approaches and actionable recommendations.
  • Analyze go-to-market funnel performance to explain what is happening, why it is happening, what it means, and what leaders should do next.
  • Define and evolve the marketing measurement framework across Marketing Mix Modelling, Multi-Touch Attribution, incrementality, experimentation, and forecasting as a unified decision-making system.
  • Lead the design and operationalization of advanced marketing measurement approaches, including Marketing Mix Modelling, Multi-Touch Attribution, incrementality testing, spend efficiency curves, saturation analysis, and diminishing returns modelling; connect marketing and channel investment to subscription revenue, customer acquisition cost, payback, lifetime value, pipeline quality, and long-term customer value.
  • Set standards for selecting, building, quality-assuring, and interpreting advanced measurement methods, including Marketing Mix Modelling, Multi-Touch Attribution, incrementality testing, causal inference, forecasting, and simpler diagnostic approaches.
  • Partner with Performance Marketing, Demand Generation, Brand Marketing & Communications, Partnerships, Finance, and Marketing Operations to evaluate spend efficiency, channel mix, conversion quality, saturation, diminishing returns, and budget allocation trade-offs, including scenario analysis ahead of planning cycles.
  • Lead analytics on funnel health, lead quality, conversion performance, representative 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 to help leaders monitor performance, diagnose issues, and make planning, resourcing, and prioritization decisions.
  • Connect sales and marketing performance into a unified view of acquisition economics to assess how demand, channel mix, sales motion, and customer quality translate into durable revenue growth.
  • 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.
  • Contribute to the Analytics 2.0 roadmap by identifying where AI, machine learning, automation, and agentic analytics can accelerate Sales and Marketing measurement, forecasting, diagnostics, storytelling, and self-serve decision support.
  • Partner with Analytics Engineering, business intelligence, 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 quality assurance.
  • 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 by validating outputs, understanding limitations, documenting methods, and using automation to create capacity for strategic modelling and business influence.

Desired Qualifications

  • Experience in a high-growth software-as-a-service or subscription business is ideal.
  • Experience with Marketing Mix Modelling libraries or statistical modelling frameworks such as Robyn, Meridian, PyMC-Marketing, Bayesian modelling frameworks, or equivalent tools is a strong asset.

About the Company

Jobber

SaaS for home-service operations management

Jobber provides a subscription-based SaaS platform that helps home service businesses manage their operations. It includes tools for creating quotes, scheduling jobs, invoicing, and collecting payments, all accessible via web and mobile apps. Automated payment follow-ups and unlimited one-on-one support help businesses maintain cash flow and keep clients on track. The platform also offers resources like salary reports to assist hiring and team retention. Compared with competitors, Jobber focuses on end-to-end workflows tailored specifically to home services (cleaning, landscaping, plumbing, HVAC, and more) plus strong customer support and onboarding. The company's goal is to enable small to mid-sized home service businesses to operate more efficiently and grow by simplifying their day-to-day processes.

Company size
1,001-5,000
Company stage
Series D
Total funding
$185.8M
Headquarters
Edmonton, Canada
Founded
2011

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