Okta
SeniorManager,RetentionStrategy&Intelligence
“Senior Manager, Retention Strategy & Intelligence at Okta. Skills: Retention Strategy, AI-powered retention, Risk signal analysis, AI model development, Cross-functional leadership. Own the development and operationalization of Guided Renewals, our AI-powered approach to proactive retention. Own the intelligence layer that drives retention: identifying and tracking risk signals, partnering with teams to build AI models that surface risk and recommend personalized interventions, and leading the f”
What You'll Achieve.
Risk scores and recommendations achieve >80% accuracy with field feedback on actionability; High, sustained engagement across field teams; Measurable lift in retention outcomes where AI recommendations are followed; Cadences running consistently with improvement in early risk identification; ARR at risk stabilized and recovered through program interventions; On-track execution against FY'27 milestones with a Phase 2 plan in place
Industry & Context.
Solve complex challenges with real-world stakes; Conduct root cause analysis on churn and contraction to identify gaps and inform future iterations
Onboarding experience is in-person
What They're Looking For.
Must Have
7+ years across Customer Success, Renewals, Sales Enablement, or Revenue Operations with hands-on experience in data, analytics, or process automation, Working knowledge of AI/ML, data architecture, and APIs, Able to engage technical teams and translate business needs into solutions, Able to design the logic and guardrails that govern AI behavior and ensure outputs are accurate and operationally useful, Connects data signals to customer realities and understands how field teams actually work, Experience defining requirements, managing roadmaps, and iterating on user feedback, Able to influence and align across Engineering, Data Science, Sales, CS, and Renewals
What You'll Do.
Own the development and operationalization of Guided Renewals
our AI-powered approach to proactive retention
Own the intelligence layer that drives retention: identifying and tracking risk signals
partnering with teams to build AI models that surface risk and recommend personalized interventions
and leading the field cadences that turn insights into action
and interpretation of customer risk signals including usage
and commercial health
Partner with TDI to establish signal weighting
and supporting data infrastructure
Translate risk analysis into clear
actionable intelligence for field teams and leadership
Define the guidelines
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
Evaluate recommendation quality and drive model refinement where AI output and business reality diverge
Own product requirements for risk and recommendation tooling
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
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
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
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
How You'll Work.
Team & Collaboration
Partner directly with our Renewals organization; Collaborate with GTM functions across the customer lifecycle; Partner with our Technology, Data, and Insights (TDI) team; Partner with TDI and Data Science to build models; Influence and align across Engineering, Data Science, Sales, CS, and Renewals; Establish feedback loops with field teams and TDI
Communication Scope
Translate business needs into solutions; Translate risk analysis into clear, actionable intelligence
Process & Methodology
Manage the roadmap from pilot to GA, Prioritizing enhancements based on field feedback and model performance
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