Synced from Greenhouse · Aug 21

Data Scientist

AlpacaRemote - Americas Posted Aug 21, 2026
Data ScientistRemoteSenior
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Mirrored from Alpaca's own Greenhouse careers system · refreshed hourly

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Aug 21
Posted
Greenhouse
Applicant system
Job descriptionReq 6020810004

Who We Are:

Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more.

Amongst our subsidiaries, Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs. This includes broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges, totalling over 10 million brokerage accounts.

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. We're deeply committed to open-source contributions and fostering a vibrant community, continuously enhancing our award-winning, developer-friendly API and the robust infrastructure behind it.

Alpaca is proudly backed by $400 million in funding from top-tier global investors including Portage Ventures, Spark Capital, Tribe Capital, Social Leverage, Horizons Ventures, Opera Tech Ventures, SBI Group, Derayah Financial, Unbound, Peak XV, Elefund, and Y Combinator.

Our Team Members:

We're a dynamic team of 400+ globally distributed members who thrive working from our favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK, and beyond!

We're searching for passionate individuals eager to contribute to Alpaca's rapid growth. If you align with our core values—Stay Curious, Have Empathy, and Be Accountable—and are ready to make a significant impact, we encourage you to apply.

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.

How We Take Care of You:

  • 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

Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.

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View original posting on Greenhouse

What applying to Alpaca usually looks like

Based on publicly available information, candidates applying through greenhouse can typically expect a structured process that starts with an online application and resume screen, often followed by a recruiter phone call to discuss background and expectations. For Alpaca, roles across engineering, product, compliance, and operations may include multiple stages such as technical or role-specific assessments, hiring manager conversations, and panel interviews with cross-functional team members. Greenhouse-based processes commonly involve standardized scorecards and structured interview questions to support consistent evaluation. Communication is generally handled through automated email updates, though response times vary depending on team bandwidth and role seniority. Candidates may also be asked to complete take-home exercises or case studies, particularly for technical or analytical positions, before proceeding to final rounds or offer discussions.

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Data Scientist
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