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We are looking for a Data Analyst who doesn't just answer questions — they can't stop asking them. You're the kind of person who pulls a report, spots something slightly off in row 47, and four hours later has uncovered a trend nobody knew existed. You're technically sharp enough to build what you need and curious enough to keep digging until the story is clear. This role sits at the intersection of rigorous analysis and modern AI. You will use LLMs, automation pipelines, and AI-assisted tooling to dramatically accelerate insight generation — but the engine behind it all is genuine intellectual curiosity and the drive to understand why, not just what. You will partner closely with product, marketing, operations, and leadership — not just to answer the questions on their roadmap, but to surface the ones they haven't thought to ask yet.
Job Responsibility
Dig into data with genuine curiosity — follow threads, challenge assumptions, and don't stop at the surface-level answer
Design and execute investigations that surface non-obvious insights, not just metric summaries
Build and maintain SQL queries, Python scripts, and data models to support recurring and ad-hoc analysis
Own key performance dashboards and proactively flag when something looks interesting — or wrong
Use LLM APIs (e.g., Claude, GPT) to automate insight generation, narrative writing, and anomaly detection
Build natural language interfaces that allow non-technical stakeholders to query data without SQL
Design and maintain AI-powered reporting pipelines that deliver weekly/monthly commentary automatically
Develop and test prompts for structured data extraction, classification, and summarization tasks
Turn complex findings into clear, compelling narratives
Come to meetings with a point of view, not just a chart
Partner with business teams to frame the right questions — and push back when the wrong questions are being asked
Collaborate with data engineering to define and document data models, transformations, and quality standards
Contribute to the team's data catalog and ensure analytical assets are documented and reproducible
Advocate for data quality, consistency, and governance across the organization
Requirements
3–6 years in a data analyst or analytics engineer role