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.Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!About the Role:As a Senior Data Analyst, you will be responsible for preparing, analyzing, and interpreting large datasets to support the development and evaluation of machine learning models. Your work will focus on ensuring high-quality data, identifying meaningful patterns, and generating actionable insights that contribute to AI-driven solutions. This role demands strong analytical skills, attention to detail, and a keen interest in working with machine learning data in a dynamic, fast-paced environment.ResponsibilitiesOwn enterprise client onboarding for agentic AI implementations, including data analysis, topic clustering, coverage planning, and workflow/action designDesign, implement, and optimize prompts, conversation flows, agent logic, and knowledge configurations for production AI agentsDeliver AI solutions end-to-end, from solution design through UAT, production launch, and post-go-live optimizationOwn post-launch AI performance at the client level, driving improvements in containment, resolution quality, and handoff reductionAnalyze conversation data, quality signals, and DSAT drivers to identify root causes and optimization opportunitiesImplement iterative improvements across prompts, workflows, actions, guardrails, and knowledge bases based on data and evaluation resultsCollaborate with AI Quality & Evaluation teams to validate response accuracy, conversation quality, and regression riskPartner with Client Analytics and ML-Ops teams to act on insights, platform changes, and production issuesMentor junior analysts and engineers through design reviews, solution feedback, and applied AI best-practice guidanceRequirement5+ years of experience in applied AI, conversational AI, analytics, or AI-powered customer experience solutionsHands-on experience with LLMs, prompt engineering, agent workflows, and tool/action-based AI systemsExperience 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 experienceWorking knowledge of SQL and Python for data analysis, experimentation, and debugging AI behaviorAbility to use Tableau, Power BI, or similar BI tools to analyze trends, quality signals, and performance metricsExperience collaborating with cross-functional teams including analytics, quality, product, and ML-OpsComfortable working directly with enterprise customers and translating ambiguous requirements into clear, scalable AI solutions