Manager, Advanced Analytics & Automation

Klaviyo
Denver, COPosted 7 April 2026

Job Description

At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny. Role Summary Klaviyo is seeking a Manager of Advanced Analytics Automation to lead strategic analytics programs and AI first automations for our Customer Success Strategy and Analytics team. This role owns the development of scalable customer intelligence systems, and spans customer cohorting, health and success signals, churn and expansion drivers, and AI-powered workflows that translate insight into action. You will operate as a senior technical individual contributor with program-level ownership , combining advanced data analytics and applied AI in partnership to build durable tools and processes used across GTM. This role is ideal for someone who can architect, build, QA, and operationalize advanced analytics and insights projects end-to-end while partnering deeply across Product, Ops, and Data teams. What You’ll Do Own Customer Success Intelligence Advanced Analytics Insights, design Production-Grade Data Models Analytics Pipelines, and champion AI Tooling, Automation Workflow Orchestration Build and maintain customer cohorting, segmentation, and benchmarking frameworks, in collaboration with our Product Data Science team, that captures meaningful differences in Customer behavior, maturity, and value Define and evolve customer health, adoption, and success scoring and signals, including leading indicators of churn and expansion Design and scale advanced analytics projects and models, including cohort analysis, statistical inference, and impact measurement systems, that connect product usage and engagement to customer retention outcomes Act as a technical program owner for complex analytics initiatives, driving roadmap definition, sequencing workstreams, coordinating dependencies, and delivering outcomes Create advanced SQL and Python outputs that power customer insights, forecasting inputs, and operational reporting, using GitHub for version control and change management, and applying strong data modeling and governance practices Partner closely with Data Engineering, CS OPs, Data Science and Product Analytics, to deliver strategic analytical tools and insights that inform GTM priorities, roadmap decisions, and customer strategy, and collaborate to deliver prototype AI-assisted tools that provide GTM teams real time actionable insights into customer behavior Design and deploy workflow automations using n8n, Airflow or other AI tools, and establish integrated AI driven alerts that surface real-time customer risk and opportunity Lead initiatives end-to-end: problem framing, design, build, QA, documentation, rollout, and iteration Maintain a high bar for execution quality, accuracy, reliability, and long-term scalability Translate complex technical outputs into clear, actionable narratives for senior business and GTM stakeholders What We’re Looking For 5+ years of experience in advanced analytics, technical analytics or data analytics (SaaS strongly preferred) Advanced proficiency in SQL and GitHub, with experience owning complex analytical data models Strong hands-on experience with Python and/or R, including statistical inference, cohort analysis, and advanced research Tableau Developer–level fluency, with solid understanding of dashboard logic, metrics, and database structures Confident using AI tooling (e.g., Cursor, Glean, Codex, GitHub AI etc.) to accelerate development, and familiarity with workflow automation platforms (n8n, Airflow, DBT); experience with LangChain a plus ... (truncated, view full listing at source)
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