Identify and prioritize growth opportunities across products
Drive results and achieve business objectives
Act as a senior lead for analysis, hypothesis generation, and experimentation
Operate autonomously across different products and domains
Support teams in data interpretation and strategy definition
Ensure continuous learning from tests and metrics
Requirements
Strong familiarity with data tools, such as:
SQL (intermediate/advanced)
Google BigQuery (BQ)
GCP environment (overview of pipelines, datasets, and costs)
Visualization tools (Looker, Data Studio, Power BI, Tableau or similar)
Ability to interpret data and metrics, such as:
Conversion funnel
Cohorts
LTV, CAC, churn, retention
Activation and engagement metrics
Product and growth metrics
Deep knowledge of the Customer Journey
End-to-end mapping (discovery → conversion → use → retention → advocacy) and identification of frictions, gaps, and growth opportunities