About the Job
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 statis...
Key Responsibilities
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.
Required Skills & Abilities
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.
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
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
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 MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
