Data Scientist, Terminal

Who we are

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

We’re working on making the global financial system programmable. This is one of the largest opportunities for impact in the history of computing, on par with the rise of modern operating systems. It is too difficult and expensive today for fast growing companies to produce financials and analyze their businesses. We are laser focused on building an end-to-end solution for users to understand their performance and grow their revenue.

What you’ll do

Responsibilities

• Define and measure key outcome metrics for products that cater to our users needs.
• Design and analyze experiments to improve the conversion funnel for product adoption and targeting efficacy.
• Apply statistical methods, causal inference, and machine learning to inform product decisions and optimize our products and systems.
• Design and develop data sets that enable better understanding of adoption and engagement.
• Partner closely with product, engineering, finance, and marketing teams to identify and prioritize the most important data science projects.

Who you are

We’re looking for an experienced data scientist to partner with teams to support the growth of our products and develop new ones. If you are excited about building new products on Stripe’s platform, live and breathe data-driven product development, and are energized by designing strategic metrics and causal analyses, then we want to hear from you.

Minimum requirements

• 6+ years of data science/quantitative modeling experience.
• A PhD or MS in a quantitative field (e.g., Statistics, Quantitative Finance, Economics, Sciences, Engineering) or equivalent experience.
• Expert knowledge of a scientific computing language (such as R or Python) and SQL.
• Expertise in statistics and experimental design.
• Prior experience with product and/or go to market data science or enthusiasm to learn.
• A demonstrated ability to manage and deliver on multiple projects with a high attention to detail.
• The ability to communicate results clearly and a focus on driving impact.