Data Scientist, Payments

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companiesfrom the worlds largest enterprises to the most ambitious startupsuse 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 everyones 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. Were 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.

What youll do

Were looking for a Data Scientist to partner with our Local Payment Methods (LPM) engineering and product teams. Youll play a key role in understanding growing and optimising our LPM business leveraging data to make strategic business decisions. As Data Scientists at Stripe its 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.

Who you are

Were 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

• PhD MSc or MA with 2 years or BS or BA with 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 builders 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)