Lead Product Data Analyst
New
J
JobgetherHome services marketplace
Based in Brazil; Workplace type: Remote, Coordinate working hours with US-based stakeholders.Full-TimeLead
Salary75,000 - 100,000 USD per year
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Job Details
- Required Skills
- PythonSQLProduct AnalyticsA/B testingdbtR
Requirements
- Bring strong experience in product analytics, business intelligence, data analysis, or a related field, operating independently at a senior or lead individual-contributor level.
- Have advanced SQL skills and practical experience with data modeling and transformation using dbt.
- Have intermediate proficiency in Python or R, particularly for statistical analysis and deeper analytical investigations.
- Have experience designing and maintaining dashboards, reporting systems, and self-service analytics solutions; familiarity with Lightdash is relevant.
- Be able to conduct experiments and interpret results, including A/B testing, retention analysis, and multivariate modeling.
- Understand marketplace dynamics and relationships among supply, demand, pricing, customer behavior, and service performance.
- Translate complex analytical findings into clear business recommendations that influence stakeholder decisions.
- Define, document, and maintain trusted metrics and reusable datasets.
- Use AI tools such as Claude, ChatGPT, or Copilot in analytical workflows and validate generated outputs.
- Work autonomously without direct people-management responsibilities.
Responsibilities
- Conduct product and marketplace analyses, including A/B testing and multivariate modeling, to identify trends and optimization opportunities.
- Investigate relationships across supply, demand, pricing, retention, estimated arrival times, and service quality.
- Develop and maintain dashboards and reporting systems with accurate, current, actionable metrics.
- Establish consistent metric definitions and documentation.
- Partner with product managers, researchers, and business stakeholders to support prioritization and evaluate initiatives.
- Build and maintain reusable, documented datasets and data models in the data warehouse using dbt.
- Improve self-service analytics by making datasets, reports, and documentation accessible to non-technical teams and providing guidance or training.
- Use AI-powered tools to support SQL development, dbt modeling, analysis, and reporting, and validate generated outputs.
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