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.

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