Data Scientist

About the role

We're looking for a Data Scientist to join our team at Stripe, where you'll work closely with our Product, Finance, Payments, Security, Risk, Growth and Go-to-Market teams.

As a Data Scientist at Stripe, you'll play a crucial role in optimizing our systems and leveraging data to make strategic business decisions. You'll work with a variety of data science roles and teams across Stripe, and will be aligned to the most relevant team based on your background.

Responsibilities

• Work closely with a specific part of the business to optimize our systems and leverage data to make strategic business decisions
• Use techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics to ensure that the company strategy, products, and user interactions make smart use of our rich data
• Partner 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

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

• PhD + 3 years, MS/MA + 6 years or BS/BA 8 years of data science/quantitative modeling experience
• Proficiency in SQL and a computing language such as Python or R
• Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
• 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
• Solid business acumen and experience in synthesizing complex analyses into actionable recommendations
• A builder's mindset with a willingness to question assumptions and conventional wisdom

Preferred qualifications

• 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.
• A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)