Data Scientist, Global Growth

Stripe; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Stripe is seeking a Data Scientist to partner with Global Growth teams to design and ship experiments, build models, and analyze impact across stripe.com and the dashboard to help businesses worldwide get started on Stripe. You’ll help us understand, grow, and optimize the self‑serve user funnel to ensure a high‑quality onboarding experience for users globally.

As a Data Scientist at Stripe, you’ll design experiments, deploy predictive models, and translate analyses into actionable insights for

Qualifications

• Bachelor's degree or higher in a quantitative field.
• 8+ years with data science or quantitative modeling in role(s).
• Proficiency in SQL and Python or R.

Responsibilities

• Design and ship experiments with Global Growth teams.
• Build machine learning and statistical models to drive impact.
• Analyze data to understand onboarding, user funnel, and revenue implications.
• Communicate results clearly to cross-functional partners.

Skills

SQL

Python

R

Cross-functional collaboration

Communication

Experiment design

Modeling

Education

Bachelor's degree

Master's degree

PhD

Tools

Spark

Hadoop

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 data scientists with a passion for analyzing data, building machine learning and 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), and how our go‑to‑market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.

What you’ll do

We’re looking for a Data Scientist to partner with our Global Growth teams. You’ll play a key role in designing and shipping experiments, as well as identifying improvement opportunities across stripe.com and the dashboard to help businesses worldwide get started on Stripe. You’ll help us understand, grow, and optimize the self‑serve user funnel to ensure a consistently high‑quality onboarding experience for users globally. As Data Scientists at Stripe, our mission is to ensure that company strategy, products, and user interactions make smart use of our rich data using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics.

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

• Bachelors + 8 years or Masters + 6 years or PhD + 3 years of data science or quantitative modeling experience
• Proficiency in SQL and a computing language such as Python or R
• Experience in working with cross‑functional teams to deliver results
• Ability to communicate results clearly and a focus on driving impact
• A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
• Strong business acumen and experience in synthesizing complex analyses into actionable recommendations
• Proficiency with AI tools to accelerate model development, analysis, and coding

Preferred qualifications

• Strong knowledge and hands‑on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation
• Experience deploying models in production and adjusting model thresholds to improve performance
• Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
• A builder’s mindset with a willingness to question assumptions and conventional wisdom
• Experience with distributed tools such as Spark, Hadoop, etc.
• A PhD or MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)