Data Analyst, Global Growth
Singapore
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and build scalable data models and infrastructure for product analytics and metrics
Own business-critical datasets and production pipelines with testing and monitoring
Build metric definitions and business context so AI agents can answer stakeholder questions
Develop dashboards, automated reporting and analyses that surface actionable insights
Turn senior leaders' business needs into analytical questions and deep-dive recommendations
From the employer’s posting
Design and build scalable data models and infrastructure to power product analytics and metrics reporting
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
Develop dashboards, automated reporting, and thoughtful analyses to surface actionable insights
Partner closely with senior business leaders to translate business needs into analytical questions and deliver clear recommendations through deep-dive analyses
What you’ll bring
All qualificationsCore experience
- 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.
- Experience with distributed data frameworks such as Spark to write and debug data pipelines
Preferred experience
- Prior experience at a growth-stage internet or software company
- Experience creating leadership-level reporting, such as quarterly business reviews and monthly business reviews
- Good understanding of development processes and best practices like engineering standards, code reviews, and testing
Qualification wording
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
Prior experience at a growth-stage internet or software company
Experience creating leadership-level reporting, such as quarterly business reviews and monthly business reviews
Good understanding of development processes and best practices like engineering standards, code reviews, and testing
Education & alternatives
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
Tools in this posting
- Python
- Scala
- SQL
- Spark
- Airflow
Source — Tool mentions in context
- 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
- 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
- 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 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
About Stripe
Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier listing.
- Status in our records
- Live
- First seen by us
- Oct 17, 2026 · 8 days ago
- Recorded sightings
- 61
- Last seen by us
- Oct 25, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on stripe.com. The employer’s form will show what is required.
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Job description
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
Source details
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- Pay
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- Location & working pattern
Singapore
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