Revenue Insights Manager

Posted Yesterday
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San Francisco, CA, USA
In-Office
180K-275K Annually
Senior level
Artificial Intelligence • Software
Building embeddings-based search infrastructure
The Role
Lead GTM analytics and reporting: define core revenue metrics, build forecasting and capacity models, create governed data models and dashboards, drive revenue cadence and board reporting, analyze segment/territory/productivity, and build AI-native automated analysis workflows.
Summary Generated by Built In
THE ROLE

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.

WHAT YOU’LL OWN

Core Revenue Reporting & Business Rhythm

  • 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.

  • Reconcile against goals: 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.

  • Forecasting: Own the analytics based forecasting motion that counterbalances against our bottoms up field forecasting rhythm. Goal is to maintain exceptional forecast accuracy

Metric Definitions & the Data Layer

  • 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

Segment, Territory & Productivity Insight

  • 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.

AI-Native Analysis

  • 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.

WHAT YOU BRING
  • 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.

WHY EXA
  • Category-defining company: Exa is the infrastructure layer for how AI accesses the world’s information — a market that barely existed two years ago and is now mission-critical.

  • Elite backing: $111M raised from Benchmark (Peter Fenton), Lightspeed, YC, and NVIDIA’s NVentures at a $700M valuation, with strong signals of continued momentum.

  • Outsized IC impact: This role has a wider blast radius than most director-level positions at larger companies. You are shaping how Exa goes to market — not optimizing someone else’s playbook.

  • AI-native culture: At Exa, AI isn’t a slide in a strategy deck — it’s the product, the infrastructure, and increasingly, how we sell. You’ll have the mandate to build the most advanced AI-led GTM motion in B2B.

  • The timing matters: Exa is at the exact inflection point where the right programs, plays, and motions will compound into durable competitive advantage. The work you do in the next 12 months will define the trajectory for the next five years.

Exa is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, veteran status, marital status, pregnancy or related conditions, criminal histories consistent with applicable law, or any other basis protected by applicable law.

Skills Required

  • 6+ years in revenue analytics, GTM/sales strategy, BI, or finance at high-growth B2B technology companies with ownership of recurring revenue reporting
  • Advanced modeling ability: capacity, funnel, quota and attainment mechanics, scenario analysis with auditable structure
  • Deep familiarity with the Salesforce data model and CRM hygiene impacts on analysis
  • Command of consumption revenue metrics including NDR, cohort windows, ARR basis and definitional edge cases
  • Experience building and owning a metrics dictionary, definitions, calculation logic, and governance across Sales, Marketing, Finance, and Product
  • Experience producing board-level revenue materials or supporting fundraise / IPO-readiness processes
  • Proficiency with SQL and Python or R for analysis beyond SQL, including cohort and propensity work
  • Experience shaping data and building reporting from tools like Clickhouse, Hubspot, Gong and reconciling multi-source data
  • Strong executive communication: clear recommendations, confidence levels, and upfront caveats
  • Comfort working as the primary/sole analytics function in a fast-moving, small-team environment
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The Company
HQ: Burlington, MA
86 Employees
Year Founded: 2021

What We Do

Exa was built with a simple goal — to organize all knowledge. After several years of heads-down research, we developed novel representation learning techniques and crawling infrastructure so that LLMs can intelligently find relevant information.

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