Data Scientist, Capital

Stripe (View all Jobs)

US Remote

Please mention No Whiteboard if you apply!
I'm a one-man team looking to improve tech interviews, and could use any support! 😄


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

R, SQL, ETL, 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

Many of the millions of businesses on Stripe have trouble accessing the capital they need to grow. Stripe Capital aims to change that. We combine Stripe’s proprietary data with sophisticated modeling to offer businesses on Stripe fair, affordable, and transparent financing. Though still in its early stages, Capital has emerged as one of Stripe’s most promising products.

We’re looking for talented data scientists to join the Capital team to help us better understand our users so we can scale Capital to support more users, new financial products, and new markets. If you are an expert working with data to empower product strategy and forecast performance, and excited to apply your experience to build new financial products, we want to hear from you.

What you’ll do

Responsibilities

  • Work closely with product, business, credit risk and engineering teams to conduct analyses and develop machine learning models to support new lending products
  • Design forecast methodology and marketing strategy to support loans and merchant cash advance products
  • Design, analyze, and interpret the results of experiments of different product strategies, to effectively manage conversion and user engagement
  • Apply statistical and analytical approaches on large datasets to (1) measure results and outcomes of our current models and product strategies, (2) understand the impact of eligibility rules on credit risk and revenue
  • Drive the collection of new data and the refinement of existing data sources to enhance our underwriting and customer management framework

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 developing machine learning or statistical models
  • Proficiency working with a scientific computing language (such as R or Python) and SQL
  • Extensive experience and passion for product analytics and experimental design
  • Strong knowledge of time series, statistics, and machine learning
  • A PhD or MS in a quantitative field (e.g. Engineering, Statistics, Economics, Natural Sciences)
  • Strong communication and presentation skills

Preferred qualifications

  • Experience with tools for working with “big data” in a distributed fashion (Spark, Hadoop, etc.)
  • Experience analyzing financial industry products
  • Experience building ETL pipelines

 

Please mention No Whiteboard if you apply!
I'm a one-man team looking to improve tech interviews, and could use any support! 😄


Get weekly alerts of new jobs from companies not using whiteboard interviews!