Signifyd’s Machine Learning team builds production ML models and risk management tools that are the core of Signifyd's product. These models are an integral part of all our products.

We help businesses of all sizes minimize their fraud exposure and grow their sales. We improve the e-commerce shopping experience for everyone by reducing the number of false positive declines of good buyers and by making fraud less profitable for criminals.

The team has end-to-end ownership of our decision-making engine, from research and development to online performance and risk management.

We value collaboration and team ownership - no one should feel they're solving a hard problem alone.

Together, we help each other develop our skillsets through peer review of experiments and code, group paper study to deepen our ML and stats understanding, and frequent knowledge-sharing through live demos, write-ups, and special cross-team projects.

How you'll have an impact:

• Research emerging fraud patterns in real-time with our Risk Intelligence team
• Improve the important components of the Signifyd Commerce Protection Platform
• Communicate complex ideas to a variety of audiences, including executives
• Build production machine learning models that identify fraud
• Write production and offline code in python, PySpark
• Work with distributed data pipelines
• Collaborate with engineering teams to strengthen our machine-learning pipeline

Past experience you'll need:

• A degree in computer science or a comparable analytical field
• 3+ years of post-undergrad work experience required
• Strong verbal and written communication skills
• Strong machine learning and statistical background, and a track record of being able to deliver under pressure.
• Write code and review others' in a shared codebase in Python
• Practical SQL knowledge
• Design experiments and collect data
• Familiarity with the Linux command line

Bonus points if you have:

• Previous work in fraud, payments, or e-commerce
• Data analysis in a distributed environment
• Passion for writing well-tested production-grade code
• A Master's Degree or PhD