Senior Data Analyst

About the Company:

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.

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

Requirement

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