Revenue Insights Manager

Exa•San Francisco, CA

1d•$180,000 - $275,000

About The Position

We're hiring a Revenue Insights Manager to own the numbers that run Exa's GTM engine. You'll build the analytics and insights layer for GTM from the ground up: the metrics definitions everyone trusts, the dashboards that turn data into decisions, and the data models underneath them. You'll partner with Data Engineering on infrastructure while owning how Salesforce, Clickhouse, Hubspot and Gong data get shaped into GTM reporting. You'll also own the data-driven cadences across the org, areas like weekly pipeline review, forecast call, QBR prep, and board reporting inputs, all which makes you the person who surfaces where the business is off-plan and why, in front of the CRO, VP Sales, and founders. This is the first Insights hire at Exa. In your first year you'll stand up the metrics dictionary, the forecast and capacity models, and the reporting stack that the next several years of GTM decisions get made on.

Requirements

6+ years in revenue analytics, GTM or sales strategy, business intelligence, or finance at high-growth B2B technology companies, with clear ownership of recurring revenue reporting.
Advanced modeling ability: capacity models, funnel models, quota and attainment mechanics, scenario analysis. Auditable structure, not heroic single-cell formulas.
Deep familiarity with the Salesforce data model and the ways CRM hygiene distorts analysis. You know where the data is wrong before you publish.
Command of consumption revenue metrics, including the definitional edge cases in NDR, cohort windows, and ARR basis — and the ability to explain them plainly to a non-technical audience.
Executive communication that lands: the recommendation, the confidence in it, and the caveats stated up front instead of buried on slide fourteen.
Intellectual honesty about uncertainty. You flag what the data cannot yet support rather than extrapolating past it.
Comfort in a fast-moving, small-team environment where you are the analytics function rather than a member of one.
Experience producing board-level revenue materials, or supporting a fundraise or IPO-readiness process.
Python or R for analysis beyond SQL, including cohort and propensity work.
Prior experience at companies selling developer tools, APIs, or data infrastructure to technical buyers.

Responsibilities

Own the recurring reporting stack: weekly business review, monthly and quarterly GTM reviews, and board-level revenue exhibits.
Produce and manage Exa’s core revenue metrics - ARR, CARR, net new ARR, NDR and GDR, logo and dollar retention, pipeline coverage, win rate, sales cycle, and segment-level performance and more.
Review our leading and lagging indicators consistently to understand how we are trending vs. our SMART goals. Use this to derive insights on what we should do next.
Own the analytics based forecasting motion that counterbalances against our bottoms up field forecasting rhythm. Goal is to maintain exceptional forecast accuracy
Own the metrics dictionary as a living contract across Sales, Marketing, Finance, and Product: definitions, calculation logic, and known caveats.
Partner with the Head of Revenue Systems & Technology on the data models and pipelines feeding analytics, so reporting runs off governed data rather than one-off extracts.
Retire duplicate and contradictory reporting. One source of truth, documented, with the old views deprecated and removed.
Build the context layer on in Clickhouse; we have all our data but adding a layer of context that allows us to build an agentic first GTM motion that is credible and actionable is key
Analyze seller productivity: ramped attainment, pipeline generation per rep, win rates by segment and account archetype, and where coverage is under- or over-invested.
Quantify ICP performance, as in which account profiles retain, expand, and convert and feed that back into targeting, territory design, and hiring plans.
Analyze cohort and retention behavior in a consumption model: usage-driven expansion patterns, contraction signals, and revenue concentration exposure.
Deliver the analysis behind territory design, account allocation, and market-entry decisions across new verticals and new regions.
Build agentic analysis workflows so leadership and the field can get trustworthy answers without waiting in your queue.
Automate the recurring analysis, so your time goes to the questions nobody has thought to ask yet.
Push the internal frontier on what AI-assisted revenue analysis looks like. We sell AI-native infrastructure and intend to operate that way.