Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the teamOur Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for a data analyst with a passion for analyzing data, statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between.
What you’ll doWe’re looking for a Data Analyst to partner with our Global organization to drive international expansion and growth. You’ll play a key role in designing and shipping experiments, owning data pipelines, and collaborating with product and engineering teams to establish the right success metrics. You will help track our progress in helping new users to go live on Stripe and empowering existing users to sell globally. Working closely with cross-functional partners, you'll extract actionable insights from Stripe's rich, complex datasets. You will also translate complex business goals into clear analytical frameworks. From building scalable dashboards to crafting compelling data narratives, your insights will directly shape how we run and grow the business.
Responsibilities- Design and build scalable data models and infrastructure to power product analytics and metrics reporting as we launch and grow new products
- Own business-critical data products, including datasets and production pipelines, ensuring reliability through rigorous testing, monitoring, and documentation
- Build and maintain the metric definitions, metadata, and business context that enable AI agents to help stakeholders explore trusted data and answer business questions independently
- Develop dashboards, automated reporting, and thoughtful analyses to surface actionable insights and proactively identify business opportunities
- Partner closely with senior business leaders to translate business needs into analytical questions and deliver clear recommendations through deep-dive analyses
- Shape product and business strategy across global markets by distilling complex findings into compelling data narratives for senior stakeholders
We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements- Bachelor’s degree and 8 years of experience, master’s degree and 6 years of experience, or PhD and 3 years of experience
- Proficiency in Scala or Python for data pipeline development, not just scripting and SQL
- Proven ability to manage and deliver on multiple projects with great attention to detail
- Ability to clearly communicate results and drive impact
- Experience with workflow orchestration tools (e.g. Airflow, Flyte, or equivalent)
- Experience with distributed data frameworks such as Spark to write and debug data pipelines
- Proficiency with AI tools to accelerate model development, analysis, and coding
- Ability to design, implement, and maintain data pipelines and dashboards to generate actionable insights based on stakeholder requirements
- Experience collaborating with cross-functional teams to deliver strategic insights, benchmarks, and analyses that provide recommendations
- Ability to enable stakeholders and partners by building self-service tooling and providing training to empower stakeholder teams to be data literate and self-sufficient in autonomous reporting capabilities
- Prior experience at a growth-stage internet or software company
- Good understanding of development processes and best practices like engineering standards, code reviews, and testing
- Working knowledge of Python
- Experience creating leadership-level reporting, such as quarterly business reviews and monthly business reviews
Skills Required
- Bachelor's degree plus 8 years, Master's degree plus 6 years, or PhD plus 3 years of experience
- Proficiency in Scala or Python for data pipeline development, beyond scripting and SQL
- Ability to manage and deliver multiple projects with strong attention to detail
- Ability to clearly communicate results and drive impact
- Experience with workflow orchestration tools such as Airflow or Flyte
- Experience with distributed data frameworks such as Spark for writing and debugging data pipelines
- Proficiency with AI tools for model development, analysis, and coding
- Ability to design, implement, and maintain data pipelines and dashboards based on stakeholder requirements
- Experience collaborating cross-functionally to deliver strategic insights, benchmarks, analyses, and recommendations
- Ability to build self-service tooling and train stakeholders to become data literate and self-sufficient in reporting
- Experience at a growth-stage internet or software company
- Understanding of development processes and practices including engineering standards, code reviews, and testing
- Strong statistical knowledge
- Working knowledge of Python
- Experience creating leadership-level reporting such as QBRs and MBRs
Stripe Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stripe and has not been reviewed or approved by Stripe.
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Fair & Transparent Compensation — Pay is commonly characterized as good, competitive, or above market, making compensation a standout aspect. High performers in particular often view overall pay favorably.
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Equity Value & Accessibility — Equity grants and, depending on role, bonuses or commissions contribute meaningfully to total compensation. Equity is frequently highlighted alongside salary as a strength.
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Healthcare Strength — Physical, mental, and medical health coverage and wellness programs are part of the core offering. These benefits are portrayed as comprehensive and competitive.
Stripe Insights
What We Do
Stripe is a technology company that builds economic infrastructure for the internet. Businesses of every size—from new startups to public companies like Salesforce and Facebook—use the company’s software to accept online payments and run technically sophisticated financial operations in more than 100 countries. Stripe helps new companies get started and grow their revenues, and established businesses accelerate into new markets and launch new business models. Over the long term, Stripe aims to increase the GDP of the internet.
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