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AI Deal Win-Loss Analysis Developer

Luna Sharma

Full-time · Job · New_York

About the role

Win-loss analysis is one of the highest-value activities in B2B sales and product strategy — and one of the least rigorously done. Most companies conduct win-loss interviews sporadically, extract themes informally, and never synthesize findings into quantitative patterns that can drive decisions. The systematic version — structured analysis across all deals with NLP-extracted themes, competitor pattern detection, and feature gap quantification — is what turns anecdotal sales feedback into strategic intelligence. We sell AI revenue intelligence to enterprise sales organizations. Win-loss analysis automation is the product capability that helps our clients learn from every deal, not just the ones they debrief on manually. We have deal outcome data and sales call transcripts. What we're building is the NLP layer that extracts structured win-loss intelligence: why customers chose us or went with a competitor, which product gaps were decisive, which objections recurred, and what sales process patterns distinguished wins from losses. You'll build the win-loss analysis automation: NLP extraction of loss reasons and win factors from call transcripts and CRM notes, competitor pattern analysis identifying which competitors appear in specific deal types, and product gap frequency analysis surfacing which feature requests appear most often in lost deals.

Responsibilities

  • Build NLP extraction of win factors and loss reasons from sales call transcripts and CRM opportunity notes
  • Implement competitor pattern analysis identifying which competitors appear in specific segment and deal-size patterns
  • Develop product gap frequency analysis quantifying which feature gaps recur most in lost deal postmortems
  • Create sales process pattern analysis correlating deal velocity, activity patterns, and outcomes
  • Build win-loss reporting dashboard for sales leadership, product management, and competitive intelligence teams
  • Develop trend tracking monitoring whether loss reasons shift as product, market, or competition evolves

Requirements

  • 3+ years in revenue analytics, sales intelligence, or data science with CRM data and NLP experience
  • Strong Python and SQL skills with text extraction, topic modeling, or classification for business document analysis
  • Understanding of B2B sales processes, deal qualification, and competitive dynamics
  • Experience translating qualitative sales feedback into quantitative intelligence products
  • Ability to present win-loss findings to sales and product audiences in terms that drive decisions

Benefits

  • Fully remote with flexible schedule
  • Health and dental insurance
  • $2,500 annual professional development budget
  • 401(k) with match
  • Performance bonus

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

AI Business, Marketing & Strategy data science & analytics

Skills

python openai api sql pandas statistics fastapi

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