Senior Data Scientist – Metrics & Analytics
🔥 0 minutes ago
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📋 Description
• Own the analytics direction of the Data Platform — define the vision, standards, and roadmap for metrics, models, and reporting delivered through the platform layer. • Unify data models across product areas — work with the Platform Reports PM and all PMs to consolidate fragmented metric definitions into a single, governed semantic layer. • Drive merchant analytics success — design, validate, and continuously improve the reports and analytics every merchant relies on to study and grow their business. • Establish documentation standards — ensure every API, dataset, metric, and column is correctly named, clearly defined, and formally documented, so definitions are consistent from the warehouse to the merchant-facing report. • Enable growth analysis — build the analytical foundations (cohorts, funnels, growth metrics, benchmarks) that let merchants and internal teams study growth accurately. • Guard data quality and consistency — define validation rules, reconciliation checks, and metric governance so numbers match everywhere they appear. • Partner cross-functionally — act as the analytical authority for the platform layer, advising engineering, product, and other analytics teams on how to build against it correctly.
🎯 Requirements
• 5+ years of experience in data science or analytics engineering, with at least 2 years in a senior or ownership-level role. • Proven experience building or governing metrics layers / semantic models (e.g., dbt, LookML, or equivalent) used by multiple teams. • Strong SQL and Python; deep comfort working directly with warehouse-level data (BigQuery, Clickhouse, Redshift, or similar). • Experience designing customer- or merchant-facing analytics products — dashboards, embedded reports, or analytics APIs. • A strong instinct for naming, documentation, and standards — you believe a well-named column and a well-written definition are product features. • Experience partnering with product managers to translate business questions into governed, reusable data models. • Excellent communication skills; able to align multiple teams around a single source of truth.
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