Lead,CustomerStrategyAnalytics&AppliedAI

## Accountabilities In this role, you will own end-to-end Customer Strategy Analytics and Applied AI initiatives that shape retention, engagement, and customer lifecycle performance across Customer Success and Support. Design and deliver data products, predictive models, and AI-powered systems such as churn risk scoring, next-best-action frameworks, and automated retention playbooks. Lead strategic analytics efforts across the customer lifecycle, partnering directly with senior leadership to define CS investment priorities and operating models. Build scalable analytics infrastructure and workflows that enable teams to act on insights without manual analysis dependency. Guide and prioritize work within your analytics pod, shaping execution done by more junior team members and ensuring alignment with strategic goals. Develop AI-enabled systems that improve CS and Support efficiency, including engagement scoring, customer health monitoring, and automation pipelines. Partner cross-functionally with Product, Sales, RevOps, Enablement, and Analytics Engineering teams to ensure data quality, modeling integrity, and business alignment. Drive adoption of AI tools and methodologies across the broader Business Operations function to accelerate analytical output and decision-making. Requirements: This role requires a strong blend of analytical depth, technical fluency, and strategic thinking, along with the ability to operate in ambiguous, high-growth environments. 5–7+ years of experience in analytics, strategy, operations, consulting, or a hybrid technical-business role. Proven track record of shipping data products, machine learning models, or AI-powered systems into production environments. Strong quantitative and analytical skills, with familiarity in SQL and/or Python considered a plus. Hands-on experience or strong familiarity with applied AI tools and agentic systems (e.g., modern LLM-based tooling). Ability to quickly understand Customer Success or Support ecosystems a