Senior Data Analyst

About the Company

Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences.

Responsibilities

• Own enterprise client onboarding for agentic AI implementations, including data analysis, topic clustering, coverage planning, and workflow/action design
• Design, implement, and optimize prompts, conversation flows, agent logic, and knowledge configurations for production AI agents
• Deliver AI solutions end-to-end, from solution design through UAT, production launch, and post-go-live optimization
• Own post-launch AI performance at the client level, driving improvements in containment, resolution quality, and handoff reduction
• Analyze conversation data, quality signals, and DSAT drivers to identify root causes and optimization opportunities
• Implement iterative improvements across prompts, workflows, actions, guardrails, and knowledge bases based on data and evaluation results
• Collaborate with AI Quality & Evaluation teams to validate response accuracy, conversation quality, and regression risk
• Partner with Client Analytics and ML-Ops teams to act on insights, platform changes, and production issues
• Mentor junior analysts and engineers through design reviews, solution feedback, and applied AI best-practice guidance

Requirements

• 5+ years of experience in applied AI, conversational AI, analytics, or AI-powered customer experience solutions
• Hands-on experience with LLMs, prompt engineering, agent workflows, and tool/action-based AI systems
• Experience working with real-world customer interaction data (chat, tickets, email, call transcripts, or voice data)
• Strong analytical ability to diagnose and resolve AI behavior issues across prompts, knowledge, workflows, evaluation, and user experience
• Working knowledge of SQL and Python for data analysis, experimentation, and debugging AI behavior
• Ability to use Tableau, Power BI, or similar BI tools to analyze trends, quality signals, and performance metrics
• Experience collaborating with cross-functional teams including analytics, quality, product, and ML-Ops
• Comfortable working directly with enterprise customers and translating ambiguous requirements into clear, scalable AI solutions