Data Analyst, Global Growth
Stripe is hiring a Data Analyst, Global Growth in Singapore, Singapore. Level rates it ; you can apply on Stripe.
Level's read on this job
- On Level's scale, this data analyst role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include SQL, AI agents and data analysis.
- Level classifies it as a mid-level role.
- Level lists 765 other open roles at Stripe.
AI in this role
Partner with Stripe's Global organization as a Data Analyst to build data models, manage pipelines, and maintain metric definitions for AI agents.
Who we are
About Stripe
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 team
Our 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 do
We’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
Who you are
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
Preferred qualifications
- 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
How we rate this
Data Analyst, Global Growth at Stripe rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data analyst jobs at this level
Pay
- Typical data analyst job
- $112k
This posting doesn't list pay. Use the typical data analyst figure when pay comes up. See data analyst jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where data analysis was part of your work. What did you do?
- Tell me about a project where experimentation was part of your work. What did you do?
- Tell me about a project where metrics was part of your work. What did you do?
- Tell me about a project where pipelines was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Data Analysis, Experimentation, Metrics, and Pipelines. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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