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As a Senior Data Analyst focused on Customer Experience (CX), you will drive data-informed improvements to customer support operations through analytics, reporting, and process optimization. You'll partner closely with CX, product, operations, and support management teams to measure performance, identify bottlenecks, and enable better decision-making across support workflows.
Key responsibilities include analyzing large-scale datasets on agent performance, support interactions, and quality assurance metrics. You'll write optimized SQL queries in BigQuery and ClickHouse, build dashboards in Tableau or Metabase, and detect behavioral and performance trends. Working with the QA team, you'll identify root causes in agent behavior and customer issues, then translate findings into actionable insights.
You'll leverage LLM tools and prompt engineering for daily analytical tasks, summarization, and insights generation. This includes assessing LLM output quality, working with LLM APIs, and integrating model outputs into analytical workflows.
Automation is central to the role. You'll use Airflow and Python to automate data tasks and optimize analytics pipelines for performance and cost-efficiency. You'll refactor inefficient DAGs, queries, and transformations, suggest improvements to agent tooling and ticket routing, and translate business inefficiencies into measurable metrics.
You'll act as an analytical partner across Operations, Support Management, QA, and Training, collaborating with Data Engineering to ensure clean, accurate data pipelines. Strong communication skills—presenting findings through visualizations and documentation to both technical and non-technical stakeholders—are essential.
Required: 3+ years as a data analyst in fast-paced, data-heavy environments; advanced SQL (BigQuery/ClickHouse); Python proficiency; experience with data visualization tools (Tableau, Metabase, Looker); understanding of Airflow and modern data pipelines; experience with LLM agents and prompt engineering; ability to translate business questions into testable hypotheses; strong presentation and storytelling skills; upper-intermediate or higher English proficiency. Experience with forecasting or machine learning is advantageous.
