Data Scientist - Authentication Optimization
Authentication is the way that a customer proves their identity before making a purchase. It plays a key role in the fundamental optimization problem at Stripe: how do we help businesses maximize the amount of good transactions, while minimizing the amount of fraud?
Europe is at the forefront of authentication due to regulatory frameworks like Strong Customer Authentication (SCA), and Stripe's global authentication effort will be centered in EMEA. We're looking for a senior data/applied scientist who will build the systems to help our users navigate SCA, and optimize their decision-making around authentication more generally.
Data science in EMEA is ramping up, and you should be excited to wear many hats.
- Research, build, and productize ML models to maximize conversion and reduce fraud for our users
- Collaborate with product and engineering to turn your work into user-facing products
- Build data sets and dashboards that help internal and external users understand payments performance and the impact of your work
- Design and implement experiments to test hypotheses and refine our understanding of the authentication ecosystem
- Influence the product roadmap through rigorous analysis and a scientific mindset
We’re looking for someone who has:
- 5+ years experience working with and analyzing large data sets to solve problems
- A PhD or MS in a quantitative field (e.g., Economics, Statistics, Engineering, Natural Sciences, Operations Research, Computer Science, or Mathematics)
- Expert knowledge of a scientific computing language (such as R or Python) and SQL
- Strong knowledge of statistics, machine learning and optimization
- Familiarity with or a desire to learn a production coding language (Ruby, Scala, or Java)
- Demonstrated track record of identifying, scoping and leading complex data science projects with cross-functional partners and high business impact
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner