Accountabilities

• Analyze the full product funnel, including onboarding, KYC, funding, and trading, to identify growth opportunities and improve key product and business metrics.
• Design and build experimentation tooling, frameworks, statistical standards, and guardrails that enable reliable A/B testing and causal-inference studies at scale.
• Define, maintain, and improve key product performance metrics in partnership with analytics engineering, ensuring they are governed, scalable, and accessible through trusted dashboards.
• Partner closely with Product, Engineering, Design, Finance, and Operations to integrate data and experimentation into the product development lifecycle.
• Translate complex datasets and analytical findings into clear visualizations, narratives, recommendations, and business insights for stakeholders and senior leadership.
• Help transition analytics from ad-hoc requests to intuitive self-service environments, including contributions to text-to-analytics capabilities built on a semantic layer.
• Mentor data scientists and analysts, establish analytical best practices, and contribute to a strong data-informed product culture.
• Identify opportunities to apply automation and emerging analytical approaches to improve the speed, consistency, and accessibility of decision-making.

Accountabilities

• Analyze the full product funnel, including onboarding, KYC, funding, and trading, to identify growth opportunities and improve key product and business metrics.
• Design and build experimentation tooling, frameworks, statistical standards, and guardrails that enable reliable A/B testing and causal-inference studies at scale.
• Define, maintain, and improve key product performance metrics in partnership with analytics engineering, ensuring they are governed, scalable, and accessible through trusted dashboards.
• Partner closely with Product, Engineering, Design, Finance, and Operations to integrate data and experimentation into the product development lifecycle.
• Translate complex datasets and analytical findings into clear visualizations, narratives, recommendations, and business insights for stakeholders and senior leadership.
• Help transition analytics from ad-hoc requests to intuitive self-service environments, including contributions to text-to-analytics capabilities built on a semantic layer.
• Mentor data scientists and analysts, establish analytical best practices, and contribute to a strong data-informed product culture.
• Identify opportunities to apply automation and emerging analytical approaches to improve the speed, consistency, and accessibility of decision-making.