Manager, GTM Analytics

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Job Posted: 08/26

Location: Americas (North, Central and South America)

Hi there!

Zapier is hiring a Manager, Analytics & Strategy to lead our newly formed GTM Analytics team. This team is the central analytics home for Marketing, Sales, RevOps, and Customer Ops, with a mandate to deliver trusted GTM insights, improve the quality and speed of decision-making, and turn repeated questions into durable self-service analytics assets.

You will manage a team of embedded analysts supporting Marketing, Sales, and Support/Customer Ops. Your team will own the day-to-day analytics interface for GTM leaders: funnel reporting, campaign performance, sales and support analytics, forecasting inputs, recurring business reviews, dashboarding, metric definitions, and urgent executive questions.

This is a hands-on analytics leadership role. we're looking for someone who has deep analytics judgment, strong SQL skills, and real GTM domain expertise. You might come from a sales analytics, marketing analytics, revenue analytics, finance, or investment banking environment. The common thread is that you know how to operate with urgency, precision, and a high quality bar, and you are energized by analytics work: scoping ambiguous business questions, pressure-testing numbers, coaching people through complex GTM data questions, and delivering clear recommendations under time pressure.

This is not a pure people-management role. You should be able to lean into advanced analytics, understand core statistical concepts, and guide work on experimentation, forecasting, or segmentation when the work calls for it, but the center of gravity is analytics leadership: trusted reporting, business partnership, analytical QA, stakeholder management, and building a faster, more consistent operating model for GTM data. You should also be AI-native in how you work and excited to make this team a proving ground for self-service analytics, analyst automation, and governed AI-assisted data workflows.

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You are a hands-on analytics manager. You have 6+ years of experience in analytics, finance, revenue operations, marketing analytics, sales analytics, business operations, investment banking, or a related field. You have managed analysts or analytics-adjacent teams for at least 1 year, but you are still comfortable rolling up your sleeves to review SQL, inspect a dashboard, pressure-test assumptions, and help frame the answer.

You have strong GTM analytics expertise. You understand how marketing, sales, customer operations, and revenue motions fit together. You have worked with funnels, pipeline, bookings or ARR, campaign performance, sales productivity, support performance, forecasting, attribution, segmentation, or lifecycle analytics. You know how to translate GTM questions into metrics, cuts, cohorts, and recommendations that leaders can act on.

You are excellent with SQL and analytical reasoning. You read and write SQL, reason about grain and joins, identify data quality issues, and coach analysts toward cleaner, more reliable methods. You are comfortable with statistics and advanced analytics concepts such as confidence intervals, incrementality, cohorting, regression, forecasting, and experiment readouts, and you know when to partner with Data Science for heavier modeling work.

You bring finance-grade rigor and urgency. You can operate in a fast-twitch environment where leaders need clear answers quickly. You know how to separate what must be directionally right today from what needs a deeper follow-up, and you keep quality high even when timelines are short. Experience in investment banking, finance, FP&A, revenue analytics, or another high-intensity analytical environment is a strong plus.

You set a high bar for quality, trust, and communication. You know that GTM analytics only works when stakeholders trust the numbers. You build review mechanisms, documentation habits, and QA standards that make dashboards and analyses easier to trust. You can explain caveats without hiding behind them, and you help teams align on source-of-truth metrics across Data, Finance, Marketing, Sales, and Customer Ops.

You are an excellent manager and coach. You raise the performance of analysts through clear expectations, thoughtful feedback, technical coaching, and strong prioritization. You know how to help analysts grow and coach them through ambiguous requests and work that should be automated or moved into self-service.

You are AI-native and automation-minded. You actively use modern AI tools to accelerate analysis, QA SQL, summarize stakeholder context, produce documentation, and prototype workflows. You are excited to make AI central to the team's operating model, and to turn repeated analyst workflows into governed self-service assets, AI primitives, reusable dashboards, or model improvements.

You can manage across analysts and data engineers. You understand the difference between stakeholder-facing analytics and data foundation work, and you help both groups work together effectively.

• Lead the Analytics & Strategy team, managing analysts embedded with Marketing, Sales, and Support/Customer Ops.

• Build a fast, trusted operating model for intake, prioritization, QA, stakeholder communication, and recurring business reviews.

• Coach analysts to deliver high-quality work across funnel reporting, campaign performance, sales analytics, support analytics, forecasting, segmentation, attribution, and executive readouts.

• Partner with GTM leaders to clarify ambiguous questions, identify the decisions at stake, and make sure the team's work leads to concrete business action.

• Review SQL, dashboards, metric definitions, data caveats, and analytical narratives so the team can move quickly without lowering the quality bar.

• Make the team the intake point for self-service and AI automation opportunities: recognize duplicate asks, separate one-off requests from repeatable workflows, and turn recurring patterns into AI primitives, governed dashboards, metric documentation, and model improvement requests that build the robot over time.

• Bring advanced analytics judgment to experimentation, incrementality, cohort analysis, forecasting, segmentation, and statistical readouts, while partnering with Data Science for deeper modeling needs.

• Leverage AI tools in your own workflow and your team's workflows, helping the team move faster while maintaining accuracy, documentation, and governance.

• Develop analysts through clear expectations, direct feedback, growth paths, and a strong peer learning culture.

The anticipated application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later, or if the position is filled.

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