Senior Manager, Retention Strategy & Intelligence

Okta Okta · Enterprise · United States · Business Operations-150

This role focuses on developing and operationalizing an AI-powered approach to customer retention, specifically 'Guided Renewals'. The Senior Manager will own the intelligence layer, identifying risk signals, partnering to build AI models for risk prediction and personalized recommendations, and leading the implementation of these insights into actionable strategies for the renewals organization. The role requires technical fluency in AI/ML, strategic thinking, and product management skills to define requirements and manage the roadmap for AI tooling.

What you'd actually do

  1. Own definition, tracking, and interpretation of customer risk signals including usage, engagement, sentiment, and commercial health.
  2. Define the guidelines, guardrails, and decision logic that govern AI-driven retention recommendations.
  3. Own product requirements for risk and recommendation tooling, defining UX, workflows, and outputs that make AI recommendations actionable for field teams.
  4. Design and lead recurring risk review cadences, including customer health reviews, that drive systematic action on AI-generated signals.
  5. Track performance across signal accuracy, recommendation acceptance, tooling adoption, and retention outcomes.

Skills

Required

  • 7+ years across Customer Success, Renewals, Sales Enablement, or Revenue Operations with hands-on experience in data, analytics, or process automation.
  • Technical Fluency: Working knowledge of AI/ML, data architecture, and APIs. Able to engage technical teams and translate business needs into solutions.
  • AI Systems Thinking: Able to design the logic and guardrails that govern AI behavior and ensure outputs are accurate and operationally useful.
  • Strategic Translator: Connects data signals to customer realities and understands how field teams actually work.
  • Product Thinking: Experience defining requirements, managing roadmaps, and iterating on user feedback.
  • Cross-Functional Leadership: Able to influence and align across Engineering, Data Science, Sales, CS, and Renewals.

What the JD emphasized

  • AI Systems Thinking
  • Technical Fluency: Working knowledge of AI/ML, data architecture, and APIs.
  • Define the guidelines, guardrails, and decision logic that govern AI-driven retention recommendations.

Other signals

  • AI models that surface risk and recommend personalized interventions
  • AI-powered approach to proactive retention
  • Define the guidelines, guardrails, and decision logic that govern AI-driven retention recommendations