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As a Senior Customer Experience (CX) Data Analyst at Tabby, you will drive data-informed improvements to customer support operations through advanced analytics and process optimization. Working closely with CX, product, operations, and QA teams, you'll measure support performance, identify operational 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 and Metabase, and detect behavioral and performance trends across support teams. You'll partner with QA to identify root causes in agent behavior and customer issues, translating business inefficiencies into trackable metrics.
This role uniquely emphasizes modern AI/ML integration: you'll use LLM tools and prompt engineering for daily analytical tasks, summarization, and insights generation. You'll assess LLM output quality and relevance in business contexts, and integrate model outputs into analytical workflows and internal tooling via LLM APIs.
Automation and optimization are core: you'll work with Airflow and Python to automate data tasks, optimize analytics pipelines and data marts for performance and cost-efficiency, and refactor inefficient DAGs and queries. You'll suggest and co-build improvements in agent tooling, ticket routing, and SLA tracking.
Required qualifications: 3+ years as a data analyst in fast-paced, data-heavy environments; advanced SQL (BigQuery/ClickHouse); Python proficiency for data analysis and automation; experience with data visualization tools (Tableau, Metabase, Looker); understanding of Airflow and modern data pipelines; hands-on experience with LLM agents and prompt engineering; ability to translate business questions into testable hypotheses; strong presentation and storytelling skills for technical and non-technical audiences; upper-intermediate or higher English proficiency.
