Job Description

Roles & Responsibilities

This role focuses on analytics, reporting, and process optimization, with exposure to automation and AI powered tools as part of everyday analytical work.

Data Analysis & Insights

• Analyze large-scale datasets related to agent performance, support interactions and QA.
  
• Write optimized SQL queries using tools like BigQuery and ClickHouse.
  
• Build dashboards in Tableau, Metabase.
  
• Detect behavioral and performance trends among agents and support teams.
  
• Partner with QA to identify root causes in agent behavior and customer issues.
  

LLM & Prompting

• Use LLM tools with practical prompt engineering for daily analytical tasks, summarization, and insights generation.
  
• Ability to assess and profile LLM outputs for quality, relevance, and analytical correctness in business contexts.
  
• Familiarity with LLM APIs and integrating model outputs into analytical or internal tooling workflows.
  

Automation & Workflow Optimization

• Work with Airflow and Python to automate data tasks and support workflows.
  
• Optimize analytics pipelines and data marts to improve performance, resource efficiency, and reliability.
  
• Identify and refactor inefficient DAGs, queries, and transformations to ensure scalable and cost-effective data processing.
  
• Suggest and co-build improvements in agent tooling, ticket routing, and SLA tracking.
  
• Translate business inefficiencies into trackable metrics and measurable outcomes.
  

Cross-Functional Collaboration

• Act as an analytical partner to Operations, Support Management, QA, and Training.
  
• Work with Data Engineering to ensure clean, accurate, and well-modeled data pipelines.
  
• Communicate findings clearly through presentations, visualizations, and concise documentation.
  

Desired Candidate Profile