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.
