Manager, Customer Analytics (Sales & Marketing)

Jobber•Toronto, ON

2d•CA$151,200 - CA$204,500•Hybrid

About The Position

Jobber is looking for a Manager, Customer Analytics (Sales & Marketing) to lead the analytics function supporting its Marketing & Channels and Sales & Partnerships pods. This role reports to the Senior Manager, Customer Analytics and will manage a team of analysts. The Manager will partner closely with Directors, Senior Directors, and VPs across various departments including Demand Generation, Brand Marketing & Communications, Sales, Partnerships, MarketingOps, SalesOps, and Finance. The primary responsibility is to set the technical, methodological, and strategic direction for high-impact Sales and Marketing analytics. This includes owning the measurement infrastructure to connect acquisition investment to revenue growth, understand marketing effectiveness, evaluate channel and partnership performance, and improve visibility into key metrics like CAC, LTV, payback, sales efficiency, revenue funnel performance, and go-to-market ROI. The ideal candidate combines strong people leadership, technical depth, and deep Sales and Marketing domain expertise. They will build trusted relationships with senior leaders, enhance analytical quality, and develop analysts to translate measurement into growth decisions. The role also involves advancing Analytics 2.0 by leveraging self-serve analytics, automation, responsible AI, and agentic workflows to scale decision support and free up capacity for strategic analytical work.

Requirements

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.
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.
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 BI tools such as dbt, Snowflake, Redshift, Looker, Tableau, or similar platforms.
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.

Nice To Haves

Experience with MMM libraries or statistical modelling frameworks such as Robyn, Meridian, PyMC-Marketing, Bayesian modelling frameworks, or equivalent tools is a strong asset.
Ability to build scalable, trusted reporting and decision-support assets.

Responsibilities

Hire, onboard, lead, coach, and develop a high-performing team of analysts supporting Demand Generation, Brand Marketing & Communications, Sales, and Partnerships.
Establish a clear engagement and prioritization model for Sales and Marketing Analytics, creating scalable operating rhythms.
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.
Lead the analytics roadmap across Jobber’s Marketing & Channels and Sales & Partnerships pods, focusing on 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 recommendations.
Define and evolve Jobber’s marketing measurement framework across Marketing Mix Modelling (MMM), Multi-Touch Attribution (MTA), incrementality, experimentation, and forecasting.
Lead the design and operationalization of advanced marketing measurement approaches, 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.
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.
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.
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 for senior leaders.
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.
Champion governed self-serve analytics and trusted metrics so Sales and Marketing leaders can answer recurring performance questions.
Help analysts adopt AI responsibly, validating outputs, understanding limitations, documenting methods, and using automation to create more capacity for strategic modelling and business influence.