Turn data into stories: surface the pattern behind an issue, propose the fix (QA process-flow change and/or automation), and own the subsequent plan and execution.
Automate performance/accuracy review processes, report generation, and data visualization using Python and SQL: building reusable, scalable workflows, not one-off scripts.
Support Engineering and Data Science on system-level data fixes. Understand how the engine makes predictions, and explore improvements by fixing or introducing new data and features.
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