Senior Manager, Retention Strategy & Intelligence

Okta•Chicago, IL

9d•$158,000 - $218,000•Hybrid

About The Position

This role is an opportunity to do career-defining work at Okta, focusing on enhancing the GTM function with AI capabilities as part of a broader retention strategy. The Senior Manager of Retention Strategy & Intelligence will own the development and operationalization of Guided Renewals, an AI-powered approach to proactive retention. This involves partnering with the Renewals organization, collaborating with GTM functions across the customer lifecycle, and working with the Technology, Data, and Insights (TDI) team. The core of the role is to own the intelligence layer that drives retention by identifying risk signals, building AI models for risk prediction and personalized interventions, and leading field cadences to translate insights into action.

Requirements

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.

Responsibilities

Own definition, tracking, and interpretation of customer risk signals including usage, engagement, sentiment, and commercial health.
Partner with TDI to establish signal weighting, scoring thresholds, and supporting data infrastructure.
Translate risk analysis into clear, actionable intelligence for field teams and leadership.
Define the guidelines, guardrails, and decision logic that govern AI-driven retention recommendations.
Partner with TDI and Data Science to build models that generate personalized playbook recommendations based on account context, risk type, and lifecycle stage.
Evaluate recommendation quality and drive model refinement where AI output and business reality diverge.
Own product requirements for risk and recommendation tooling, defining UX, workflows, and outputs that make AI recommendations actionable for field teams.
Manage the roadmap from pilot to GA, prioritizing enhancements based on field feedback and model performance.
Ensure integration with CRM, ERP, and existing tools to minimize friction and drive adoption.
Design and lead recurring risk review cadences, including customer health reviews, that drive systematic action on AI-generated signals.
Embed cadences into Territory Planning, WIN Labs, and renewal cycles through clear workflows and supporting materials.
Serve as the primary field advocate, ensuring recommendations reduce cognitive load and drive decisive action.
Track performance across signal accuracy, recommendation acceptance, tooling adoption, and retention outcomes.
Establish feedback loops with field teams and TDI to continuously refine model logic and system design.
Conduct root cause analysis on churn and contraction to identify gaps and inform future iterations.