About the company
Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more. Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs. Our global team is a diverse group of experienced engineers, traders, and brokerage professionals who are working to achieve our mission of opening financial services to everyone on the planet.
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.
- 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.
Requirements
- 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.
Conditions
- Competitive Salary & Stock Options
- Health Benefits
- New Hire Home-Office Setup: One-time USD $500
- Monthly Stipend: USD $150 per month via a Brex Card