Company | Stripe |
Job title | Machine Learning Engineer, Fraud Discovery |
Job location | South San Francisco HQ, New York, or Seattle |
Type | Full Time |
Responsibilities:
- Designing, training, improving & launching machine learning models using tools such as XGBoost, Tensorflow, and PyTorch.
- Propose and implement ideas that directly impact Stripe’s top-line metrics.
- Propose new feature ideas and design data pipelines to incorporate them into our models
- Improve the way we evaluate and monitor our model and system performance
- Work with product and engineering partners, as well as risk and policy teams to build solutions that fit product needs.
- Collaborate with stakeholders and drive end-to-end projects involving a variety of technologies and systems to successful completion.
Requirements & Skills:
- 3+ years of industry experience doing software and model development on a data or machine learning team in a production environment
- Have experience in Python, Scala (Spark)
- Experience designing and training machine learning models to solve critical business problems
- Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, and slicing and dicing data to evaluate a hypothesis
- Hold yourself and others to a high bar when working with production systems
- Take pride in taking ownership and driving projects to business impact
- Thrive in a collaborative environment
- An advanced degree in a quantitative field (e.g. stats, physics, computer science)
- Experience in the fraud or risk space
- Have experience in Ruby
- Familiarity with NLP