Data Scientist II

Summary

Join Signifyd's Data Science team and build machine learning models for our fraud detection engine. We're looking for a curious and collaborative data scientist with 3+ years of experience in hands-on statistical analysis, experiment design, and coding (Python and Java). You'll build production models, design algorithms, research fraud patterns, work with distributed data pipelines, and communicate findings effectively. We value a tenacious and customer-passionate approach, working collaboratively to improve our fraud protection platform at scale. The role involves mentoring team members and requires a Bachelor's degree in a relevant field; an advanced degree is a plus. The position offers remote work flexibility.

Requirements

• Bachelor's degree in computer science, applied mathematics, economics, or an analytical field
• At least 3+ years of experience
• Hands-on statistical analysis with a solid fundamental understanding
• Designing experiments and collecting data
• Writing code and reviewing others’ in a shared codebase, preferably in Python and Java
• Practical SQL knowledge
• Familiarity with the Linux command line
• Fluent in English

Responsibilities

• Building production machine learning models that identify fraud
• Designing new algorithms that optimize all the key components of the Signifyd Commerce Protection Platform
• Writing production and offline analytical code in Python and Java
• Researching real-time emerging fraud patterns with the Risk Analysis team
• Working with distributed data pipelines
• Communicating complex ideas effectively to a variety of audiences
• Collaborating with engineering teams to continuously strengthen our machine learning pipeline
• Mentoring other members of the team

Preferred Qualifications

• An advanced degree (M.S. or Ph.D) in an analytical field
• Data analysis in a distributed environment
• Passion for writing well-tested production-grade code
• Using visualizations to communicate analytical results to stakeholders outside your team
• Previous work in fraud, payments, or e-commerce

Benefits

#LI-Remote