Senior Product Data Scientist

Responsibilities

• Drive product strategy with analytics. Perform deep-dive analyses across the product funnel (onboarding, KYC, funding, trading) to identify growth opportunities and drive improvements in core product and business metrics.
• Build the experimentation engine.
• Design and build the tooling, frameworks, and guardrails that empower teams to run trustworthy A/B experiments and causal-inference studies at scale—standardizing metrics, statistical methods, and self-serve analysis so the whole org can experiment with rigor and velocity.
• Define the metrics that matter. Define and maintain key product performance metrics; partner with analytics engineering to build governed, scalable metrics and dashboards that teams rely on every day.
• Embed cross-functionally.
• Partner closely with Product, Engineering
• Design, Finance, and Operations to integrate data-driven decision-making into the product development lifecycle.
• Turn data into narrative.
• Create compelling data visualizations and narratives to communicate insights and recommendations to cross-functional partners, stakeholders, and senior leadership.
• Enable self-serve and agentic analytics. Help operationalize analytics—transitioning ad-hoc requests into intuitive self-serve environments and contributing to text-to-analytics on top of our semantic layer.

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