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Описание: |
We are looking for a Senior Data Analyst to join our Identity team.
This is not a classic BI/dashboard role. You will work on large-scale identity resolution, AI scoring systems, data quality, and product decision-making.
We process 70+ TB of data and run 20M+ enrichment operations daily across multiple data sources.
You will work directly with Product and Engineering and own analytics for one of the core business domains.
What You’ll Do
* Build frameworks to measure data quality, match rates, AI scoring accuracy, ROI
* Analyze and improve LLM-based scoring systems together with engineers
* Compare external data providers and identify highest-value sources
* Investigate mismatched / conflicting data across systems
* Support internal teams with audience, campaign, and performance analysis
* Detect pipeline or provider quality issues early and drive fixes
* Turn ambiguous business questions into clear decisions
Requirements
* 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team — not consultancy, not BI-only roles.
* Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. Can read and write complex queries on tens of terabytes without someone pre-modelling the data.
* Python for analysis at a working level — pandas, Jupyter, or equivalent. Can write a small script or helper when an existing tool doesn’t cover the case.
* Built measurement or evaluation frameworks from scratch for systems with no baseline — candidate defined what to measure and how, not consumed someone else’s KPI.
* Comfort with probabilistic systems — understands noise, ranking, scoring, and that 100% accuracy is not a goal.
* AI-native workflow — uses Claude Code, ChatGPT, Copilot, or similar AI tools daily in their process.
* English: B2+ (Upper-Intermediate) or higher.
Strong Plus
* LLM evaluation / prompt testing
* Identity graph / AdTech / MarTech experience
* Healthcare / pharma data experience
* A/B testing / experimentation
We Offer
* Fully remote
* Flexible hours (CET ±2 overlap)
* High ownership / direct impact
* AI-native environment
* Fast decisions, low bureaucracy
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