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Open 7 months, first seen by us 214 days agoBuild machine learning and statistical models for products and business decisions
Design and analyze experiments and causal inference studies
building machine learning and statistical models
running experiments to drive impact
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
Proficiency with AI tools to accelerate model development, analysis, and coding
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
Experience with distributed tools such as Spark, Hadoop, etc.
Minimum requirements - PhD with 3 years, MS or MA with 6 years, or BS or BA with 8 years of data science or quantitative modeling experience - Proficiency in SQL and a computing language such as Python or R
- Experience with distributed tools such as Spark, Hadoop, etc. - A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
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
Open 7 monthsWe first saw this posting 214 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 214
Up longer than most. Similar jobs usually come down between day 8 and day 60.
Well past Stripe’s usual: its jobs come down by about day 60.
From 11,873 similar postings that came down, and 46 of Stripe’s. Coming down is not always a hire.
35 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- PhD with 3 years, MS or MA with 6 years, or BS or BA with 8 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
- 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 MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
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Yes. We’ve followed 2 other Data Scientist jobs there since April 2026. All 2 are still up.
New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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.
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), 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.
We're looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the 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.
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.
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