Jobs Companies Cogent Security Sales Operations Analyst

À propos de ce poste Sales Operations Analyst chez Cogent Security

Cogent Security · Hybride · New York, NY

Role Overview

Cogent is building autonomous cyber defense with AI agents that help security teams move from finding risk to actually fixing it. As our Sales team scales, we are hiring a Sales Operations Analyst to bring operational rigor to the revenue engine: pipeline hygiene, forecasting support, trusted reporting, CRM workflows, and AI-native systems that help reps and leaders run the business.

This role sits within the Revenue Operations arm of Growth and partners closely with Sales leadership, AEs/SDRs, Demand Gen, Finance, Enablement, and GTM Engineering. The mandate is to make the funnel measurable, trusted, and easier to operate while helping build a world-class AI-native revenue function.

This is a hands-on, high-leverage role. In the first few months, you will clean up core HubSpot reporting, improve pipeline and stage hygiene, support forecast/pipeline reviews, and partner with GTM Engineering to build workflows, reports, and assets that improve data quality, reduce rep admin, and show where the business is working or breaking.

Ownership Areas

Pipeline and Forecast Operations

  • Support pipeline reviews, forecast calls, and weekly revenue reporting with accurate data, clear summaries, and follow-up tracking.

  • Monitor stage progression, conversion rates, sales cycle length, deal slippage, stale opportunities, close-date hygiene, and loss reasons.

  • Partner with Sales leadership and AEs to improve pipeline inspection, deal movement, and accountability without adding unnecessary admin work.

  • Help maintain target account, territory, ownership, and routing logic as the team scales.

CRM, Data, and AI-Native Operations

  • Own day-to-day HubSpot hygiene for required fields, lifecycle/stage accuracy, source attribution, account/contact quality, and data completeness.

  • Partner with GTM Engineering to design, test, and roll out workflows that improve fill rates, enforce required fields, flag stale or low-quality data, and reduce manual cleanup.

  • Build and maintain dashboards for funnel conversion, rep activity, meetings, SQLs, POVs, pipeline, forecast, and source performance.

  • Document core GTM processes and handoffs across Demand Gen, SDR, Sales, Finance, and Enablement.

  • Use AI to accelerate data cleanup, enrichment QA, report generation, pipeline notes, account/deal summaries, and operating follow-up.

GTM Insights, Assets, and Operating Support

  • Translate messy sales data into insights the team can act on: where conversion drops, which sources progress, where deals stall, and what needs follow-up.

  • Support QBRs, pipeline reviews, board/leadership reporting, and ad hoc analysis.

  • Build lightweight operating assets such as pipeline review templates, deal inspection views, forecast notes, lead-to-SQL reports, rep follow-up trackers, and performance scorecards.

  • Partner with Demand Gen on lead-to-SQL performance and with Enablement on adoption, process gaps, rep behavior, and field feedback.

  • Use AI and automation to speed up reporting, analysis, asset creation, data cleanup, and operating follow-up while maintaining high judgment on quality.

What We Are Looking For

  • 2-4+ years in Sales Operations, Revenue Operations, GTM Operations, business operations, analytics, or a similar role in B2B SaaS or technology.

  • Strong understanding of SaaS GTM metrics, pipeline mechanics, forecast support, CRM hygiene, and sales process discipline.

  • Hands-on experience with HubSpot or Salesforce, dashboards/reporting, Excel/Google Sheets, and ideally Gong, enrichment tools, or BI tools.

  • Analytical and detail-oriented, but practical: you know the goal is better decisions and cleaner execution, not reporting for reporting's sake.

  • Strong communicator who can work with Sales leaders, reps, Finance, Demand Gen, Enablement, and GTM Engineering.

  • Bias for automation and AI-enabled workflows that save time, improve data quality, improve accuracy, and make the business easier to run.

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