Sales Ops / AI Analyst

Thrive

About The Position

This role sits at the intersection of sales operations and AI-driven process design. You will own sales analytics and reporting, and you will build AI agent workflows that automate manual work and improve rep and team performance. You need to be sharp with data and comfortable building tools, not just requesting them.

Requirements

3+ years in sales operations, revenue operations, or business analytics.
Strong SQL and Excel/spreadsheet skills. Experience with BI tools (Tableau, Looker, Power BI) required.
Hands-on experience building AI agent workflows or automations (tools like n8n, Zapier, Make, Hatz, or similar; prompt engineering experience a plus).
Salesforce experience including reporting and workflow/automation setup.
Experience with territory planning, account segmentation, or capacity modeling.
Proven ability to turn messy data into clear, actionable insight.
Strong project management skills. You can scope a problem, build a solution, and ship it without heavy oversight.
Comfortable driving change with sales leadership and reps.

Nice To Haves

Python and API integration experience
Experience designing human-in-the-loop workflows and evaluation methods for LLM outputs
You have built something before, a dashboard, a bot, an automated workflow, that measurably saved time or improved a number leadership cared about.
You are naturally curious about data and naturally impatient with manual work.
You can explain a complex analysis in one sentence to a VP.

Responsibilities

Own sales operations, reporting pipeline, forecast, conversion rates, win rates, quota attainment, and rep productivity metrics.
Build dashboards and reports that leaders use to make decisions.
Analyze territory capacity and coverage to identify white space, overloaded reps, and underutilized segments.
Support account segmentation and territory design using data (firmographics, account potential, historical performance).
Identify process breakdowns and inefficiencies across the sales cycle using data, not guesswork.
Partner with sales leadership to translate business problems into automated solutions.
Maintain and improve CRM data quality and workflow logic.
Document workflows and processes so they are repeatable and maintainable.
Build AI agents and automations that improve Sales Ops execution: data capture, call and meeting summaries, follow-up drafting, account research, deal risk flags, and forecast narrative support.
Create multi-step agent workflows that connect CRM, email, calling tools, and data sources.
Own an AI automation backlog and ship improvements weekly based on measurable impact.
Define guardrails: where humans must approve, what gets logged to CRM, and how we prevent bad data from spreading.
Monitor performance (accuracy, adoption, time saved, pipeline impact) and continuously iterate.
Automate dashboards and reporting for pipeline health, funnel conversion and rep activity, attainment.
Diagnose bottlenecks and quantify impact, then deploy AI or process changes to fix them.
Track ROI of automations: hours saved, speed-to-lead, conversion lift, data completeness, forecast variance.
Deliver clear insights to CRO and sales leaders with recommended actions.