Your Role:
We're looking for a Senior Data Scientist, Product to help shape Alpaca's products through rigorous product analytics, experimentation, and data-informed strategy. You'll be a senior individual contributor embedded with Product, Engineering, and Design—turning ambiguous product questions into clear insight, defining the metrics that matter, and building the experimentation tooling that lets teams decide what we build next. Your work will directly influence the roadmap, improve the developer and end-user experience across our partners, and uncover new growth and monetization opportunities across our 10M+ brokerage accounts.

This role is ideal for someone with a strong product analytics background who thrives cross-functionally, loves experimentation and causal inference, and wants meaningful ownership over how data drives product decisions at a fast-growing, global brokerage-infrastructure company. As we build a more agentic Alpaca, you'll also help make analytics self-serve for the whole company.

What You'll Do

• 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.
• Mentor and set standards. Mentor other data scientists and analysts, contribute to best practices, and help foster a data-informed product culture across the organization.

What We're Looking For

• Proven expertise in product analytics and data science, with a strong background in statistical analysis and experimentation.
• Experience building experimentation tooling and frameworks that empower teams to run trustworthy A/B tests and causal-inference analyses.
• Strong cross-functional collaboration and communication skills; able to influence product direction with both technical and non-technical partners.
• Strong programming skills in Python & SQL, or other relevant languages.
• Outstanding problem-solving skills and the ability to think critically and creatively.
• Experience with data visualization tools and techniques.
• Ability to successfully implement projects and compete in a fast-paced environment.
• PhD or master's degree in a quantitative field such as mathematics, statistics, engineering, economics, or natural sciences, and at least 6–10 years of experience developing and deploying predictive models.