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Data Scientist, Credit Risk

Stripe


1 month ago

Job type: Full-time

Remote (USA Only)

Hiring from: USA Only

Category: Data


Enable Stripe’s growth and mitigate credit risk with modeling, data, and experiments

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. Enabling the realization of this opportunity and simultaneously controlling our credit risk exposure, the Credit Risk team plays a critical role in the company’s financial health. 

We’re looking for an experienced data scientist to partner with the Credit Risk team as well as our Merchant Intelligence team to drive the use of data and modeling to measure and limit our credit risk, ensure high-quality decisions, and point towards future opportunities. The ideal candidate has experience in credit risk modeling, thinks creatively about measurement that leads to actionable outcomes, and values rigor in experimentation and modeling. 

 

You will:

  • Develop statistical and machine learning models as well as simulations to measure the full distribution of credit risk outcomes and detect potential credit risk
  • Design fully automated systems that capture risk across millions of users in 120+ countries
  • Use data and models to support the development of risk mitigation strategies and interventions while preserving and improving the user experience
  • Evolve our risk metrics, the datasets to support them, and the measurement of causal impact of initiatives to improve them
  • Develop and communicate the metrics narrative to Risk leaders 
  • Shape and influence our data models and instrumentation to generate insights and develop new data products and models

 

You’d ideally have:

  • 5+ years of data science/quantitative modeling experience, including 3+ years experience in credit risk modeling 
  • A PhD or MS in a quantitative field (e.g., Statistics, Quantitative Finance, Economics, Sciences, Engineering)
  • Strong working knowledge of SQL, R, Python, Matlab, C++, or equivalent
  • Strong understanding of financial industry models and experience building and calibrating those models to fit specific business needs  (e.g. Value-at-Risk, simulation, credit risk modeling)
  • Expertise in statistics and experimental design
  • A demonstrated ability to manage and deliver on multiple projects with a high attention to detail

Before you apply, please check if any restrictions apply in terms of time zone or country.

This job has a geo-restriction in place: USA Only.

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