Description
ABOUT THE JOB
Your mission: own that eval loop across every AI product we ship — pre-launch quality gates, post-launch monitoring, continuous improvement
You’ll work directly with our AI Quality lead, Igor KolodkinClose collaboration with AI engineers, Product, and domain experts across the company
Core stack: Databricks, DeepEval, Claude Code
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Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics
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Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency
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Close the production feedback loop: mine failure patterns from real traffic → turn them into regression cases → propose fixes to Product and domain experts
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Harden methodology: judge stability, non-determinism handling
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Translate numbers into decisions – weekly syncs, clear trade-offs, no dashboards for their own sake
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Python and SQL — you can build an analysis end-to-end
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Solid foundation in statistics — sampling, hypothesis testing, variance, understanding what a noisy metric is
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Analytical mindset — you start from the business question, not from the tool
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3+ years in analyst / data scientist roles, at least one in a product context
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Experience in quality analytics for ML systems — ranking, recommendations, classification, etc.
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Hands-on experience evaluating LLM applications (RAG, agents, tool use, judges)
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Experience building LLM agents — side projects, toy builds, personal experiments all count
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AI-assisted coding is our default authoring environment, not a bonus
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Claude Code is our main tool — you’ll reach for it for SQL, Python, analyses, dashboards, and internal scripts
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We’re looking for analysts who are already curious and fluent with AI coding — or genuinely excited to become fluent fast
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We care about what you ship and how clearly you think
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If this idea excites you rather than worries you, you’ll feel at home here
Are you interested in this position?
Apply by clicking on the “Apply Now” Button below!
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