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Interview Process
1. Programming/debugging phone screen
2. On-site with your own laptop/setup and full access to internet. Interviews include systems design, 45 min practical coding question, integrating an API exercise, debugging, and talking with hiring manager about team alignment.
Programming Languages Mentioned
ETL, SQL, R, Python
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. The Risk team plays a critical role in the company’s financial health, by enabling the realization of this opportunity while simultaneously controlling risk.
What you’ll do
Responsibilities
Act as an embedded partner to the Risk team, identifying and solving complex and ambiguous questions with data and modeling
Plan and execute with partner teams on modeling initiatives to increase accuracy, automation, and explainability
Build statistical and machine learning models to measure all aspects of risk
Create metrics and dashboards for key performance indicators and deep dive to understand the drivers of those indicators
Effectively communicate the outcomes of your analysis to key stakeholders
Who you are
We’re looking for an experienced data scientist to partner with the Credit Risk team to drive the use of data and models to measure and limit our credit risk, ensure high-quality decisions, and point towards future opportunities. If you are data curious, excited about modeling and deriving insights from data, and motivated by having an impact on the business, we want to hear from you.
Minimum requirements
5 - 7+ years experience 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 (Python or R) and SQL
Strong knowledge and hands-on experience with machine learning, statistics, and experimentation
Experience in building scalable ETL solutions utilizing SQL, Presto, Spark and other tools
Experience in working with multiple cross-functional teams to deliver results
The ability to communicate results clearly
Please mention No Whiteboard if you apply! I'm a one-man team looking to improve tech interviews, and could use any support! 😄
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