Data Scientist, Risk Operations

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.

What you’ll do

With all this data, we’re looking for a talented data scientist to join the Data Science team to help us better understand our users, build better products, and optimize our operation, with the opportunity to save Stripe millions of dollars per year. If you are data curious, excited about deriving insights from data, and motivated by having an impact on the business, we want to hear from you!

Responsibilities

•  Act as an embedded partner to the Risk Operations team, helping them to identify and answer questions with data and modeling
• Build statistical and/or machine learning models to forecast Stripe’s risk review volume across review types and use the output to help develop capacity plans
• Create simulations and/or solve optimization problems to inform the best allocation of staffing resources
• Quantify quality gaps in manual reviews
• Build and improve data ETL pipeline to collect new data and refine the existing data sources
• Design, analyze, and interpret experiments
  

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

• 5+ years experience working with and analyzing large data sets to solve problems and drive impact
• A PhD or MS in a quantitative field (e.g., Operations Research, Economics, Statistics, Sciences, Engineering)
• Expert knowledge of a scientific computing language (such as R or Python) and SQL
• Strong knowledge of statistics and experimentation
• Experience working with multiple cross-functional teams to deliver results
• The ability to communicate results clearly

Preferred qualifications

• Experience with tools for working with “big data” in a distributed fashion (Spark, Hadoop, etc.)