Revenue Operations Manager

About the role

As Revenue Operations Manager for Enterprise GTM, you will own the measurement layer of our go-to-market engine. You will be the key to what is in the pipeline, what is converting, what is slipping, and, most importantly, why, and the . Your primary customers are our enterprise new logo and expansion teams across healthcare and life sciences, financial and professional services, TMT and energy, and public sector.

We treat go-to-market as an engineered system. Architecture and design sit with the Director you report to. Instrumentation, measurement, and diagnosis sit with you.

This is an individual contributor role with a wide mandate and real exposure. You will not manage a team. You will own numbers that go to the VP of Enterprise GTM, the executive staff, and the board.

 

What you'll do

Own the enterprise reporting layer

• Build and maintain dashboards that give real-time visibility into pipeline health, stage conversion, sales velocity, coverage ratios, and attainment against plan, cut by vertical, segment, and rep.
• Establish a single agreed definition for every core metric (pipeline created, qualified pipeline, coverage multiple, win rate, cycle time, ACV, committed vs. consumed) and defend it. One number, one source, one definition.
• Report bookings, recognized revenue, and consumption as the distinct measures they are, and make the bridge between them legible to people who do not live in the model.
• Run the operating cadence: weekly pipeline reviews, forecast calls in Salesforce and Clari, MBRs, QBRs, and the enterprise section of board reporting.
• Build stakeholder-specific, self-serve views so vertical leaders, sales development, and partnerships can answer their own routine questions without opening a ticket with you.

Turn the data into insight

• Answer the hard "why" questions, e.g., why Stage 3 conversion dropped in financial services, which sourcing motions produce the highest-ACV enterprise deals, where multi-year agreements stall in legal review.
• Build leading indicators and early-warning triggers so leadership sees a coverage or velocity problem 60 days out rather than in the last week of the quarter.
• Pressure-test the forecast. Deliver an independent bottoms-up call and be willing to disagree with the field's number in front of senior leaders.
• Diagnose where to reallocate capacity, headcount, and pipeline generation effort across verticals, and bring the recommendation, not just the chart.
• Produce the analysis behind strategic bets: segmentation changes, territory restructuring, pricing and packaging shifts, new vertical entry.

Instrument the funnel and the systems that feed it

• Own top-of-funnel reporting for Sales Development: lead conversion loops, sourced vs. influenced pipeline, meeting-to-opportunity rates, and adherence to the Sales Development Playbook.
• Champion CRM data integrity. Set and enforce completeness standards for qualification fields, next steps, close dates, and competitive tags. No insight survives a dirty pipeline.
• Work hands-on in the GTM stack: Salesforce, Clari, Outreach, ZoomInfo, LinkedIn Sales Navigator, and Clay.
• Partner with GTM Engineering to automate reporting and enrichment, and use AI aggressively to compress your own analysis cycle, e.g., signal-based enrichment, automated variance commentary, first-draft narratives for business reviews.

Support planning and compensation

• Support the Director of Enterprise GTM Architecture through annual and quarterly planning: capacity modeling, territory design, headcount planning, and quota setting.
• Partner with Finance and Legal on the design and modeling of Enterprise and Sales Development commission plans, and own the reporting that tracks whether those plans are driving the intended behavior.

 

Who you are

• 8+ years in revenue operations, sales operations, GTM strategy, or a highly quantitative business operations role at a high-growth B2B SaaS, PaaS, or AI infrastructure company. Time in management consulting, investment banking, or PE counts toward this when paired with in-house operating experience.
• Analytically hands-on. Deep Salesforce reporting fluency, strong command of at least one BI layer (Looker, Hex, Tableau, Sigma), and comfort writing SQL against a warehouse (Snowflake, BigQuery, Databricks). You build the analysis yourself.
• Enterprise sales fluency. You know pipeline coverage math cold, you have worked inside a stage-gate qualification framework such as MEDDIC, and you understand what actually moves a seven-figure, multi-threaded, multi-year deal.
• A track record of reporting people use. You have built dashboards that changed decisions, not dashboards that nobody opens. You can tell the difference and you optimize for the former.
• Structured under ambiguity. You can take a vague, badly-posed question, structure it from scratch, find the root cause, and build a system that keeps it from recurring.
• Commercially and technically curious. You will need to speak credibly about our AI products, our differentiators, and the objections enterprise buyers raise around deployment, security, and data.
• Persuasive with executives. You can challenge the field's forecast with data in a room of senior leaders and keep the relationship intact.
• Genuinely interested in using AI to do this job better, not just to report on selling it.

Nice to have

• Experience in a business with a mixed revenue model (services, platform, consumption) where bookings, revenue, and recognized revenue diverge meaningfully.
• Experience supporting regulated verticals (healthcare and life sciences, financial services) or public sector, where procurement cycles and compliance gates distort the funnel.
• Experience standing up reporting for a sales development organization from scratch.

 

What success looks like

By 90 days. Core metric definitions are agreed and documented. Weekly enterprise pipeline review runs off a single dashboard you own. You have found and named at least one thing about the funnel that leadership did not know.

By 6 months. Leadership has leading indicators for coverage and velocity by vertical. Your forecast call is one leadership actively wants to hear. Data completeness standards are enforced and measurably improving.

By 12 months. Enterprise reporting is largely self-serve. Your time has shifted from producing reports to answering the strategic questions that shape next year's plan.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$207,200—$259,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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