Revenue Operations Analyst: AI-Driven Insights

Station70, Inc.

United States

Hybrid

USD 70,000 - 100,000

Full time

14 days+

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Job summary

Station70 is seeking a data-driven CRM analytics specialist to own reporting and ensure clean data in our revenue engine. You will build forecasts, attribution, and conversion-rate analytics, and contribute to AI-assisted call insights and account monitoring.

A passion for data quality and startup pace will help you thrive in a fast-moving environment. You will partner with sales and marketing to improve pipeline hygiene, renewals tracking, and performance metrics, using HubSpot as the core

Qualifications

  • Experience with HubSpot CRM and analytics.
  • Strong SQL or advanced spreadsheet capabilities.
  • Interest in AI-assisted workflows and data quality.

Responsibilities

  • Build the reporting layer: forecasts, partner attribution, win loss analysis, and conversion rates.
  • Help build and validate LLM powered tools for call insights and account monitoring.
  • Run pipeline hygiene programs: aging analysis, renewal tracking, and data quality reviews.

Skills

HubSpot expertise
SQL
Advanced spreadsheet skills

Job description

Careers / All roles

Revenue Operations Analyst
Go to market Remote (US) Full time

Make the revenue engine measurable and honest. Own CRM integrity, pipeline analytics, and the AI assisted workflows that make the commercial team faster.

What you will do

Own HubSpot: data hygiene, deal stages, pipeline configuration, and reporting dashboards.

Build the reporting layer: forecasts, partner attribution, win loss analysis, and conversion rates.

Help build and validate LLM powered tools for call insights and account monitoring.

Run pipeline hygiene programs: aging analysis, renewal tracking, and data quality reviews.

What we look for

2 to 5 years in revenue operations or business analytics at a B2B SaaS company.

Deep HubSpot expertise; SQL or advanced spreadsheet skills.

Genuine interest in building AI assisted workflows.

Detail obsession, low tolerance for dirty data, and startup adaptability.

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