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

Stripe’s mission is to increase the GDP of the internet. We build the most powerful and flexible tools for running an internet business. We handle billions of dollars each year and enable millions of users around the world to scale faster and more efficiently by building their businesses on Stripe.

What you’ll do

• Act as an embedded partner to the Risk product and engineering teams, helping them identify and answer questions with data
• Create analyses that tell a story focused on actionable insights, not just data
• Provide valuable insights through ad-hoc analyses, as well as drive long-terms projects
• Develop key performance metrics for the business, and be in charge of visualization design and implementation
• Work cross-functionally with different engineering, product and business teams
• Communicate key findings to leadership and make recommendations around risk and product strategies
• Build and improve data ETL pipelines to collect new data and refine existing data sources

Who you are

We are looking for a talented data analyst to join the Risk Data Science team and partner with the Risk product and engineering teams. The Risk team plays a critical role in helping keep Stripe safe. You’ll work on building observability, analyzing strategy effectiveness and creating scalable solutions to help us better understand our users, build better products, and optimize our operation. If you are data curious and motivated by making a high impact on the business, we want to hear from you!

Minimum requirements

• A degree in a quantitative field (e.g., Statistics, Economics, Math, Sciences, Engineering)
• 5+ years of data analysis experience
• Extensive experience and passion for metrics and dashboards visualizations
• Highly skilled at writing SQL to query relational databases; knowledge of Spark and R or Python is a plus
• Experience in building scalable ETL solutions utilizing SQL, Presto, Spark and other tools
• Experience in experiment design and analysis
• Strong communication and presentation skills
• Experience working with multiple cross-functional teams to deliver results