Data Scientist II

Summary

Join Signifyd's Data Science team and build machine learning models for our fraud detection engine. You will be hands-on, taking solutions from brainstorm to deployment, working with a diverse team. As a Data Scientist, you will build production machine learning models, design new algorithms, write analytical code in Python and Java, research fraud patterns, and work with distributed data pipelines. You will also communicate complex ideas and collaborate with engineering teams. Mentoring other team members is also part of the role. The ideal candidate will have a Bachelor's degree in a relevant field, 3+ years of experience, and strong analytical and coding skills.

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
• Working directly with Go-to-Market teams
• Previous work in fraud, payments, or e-commerce

Benefits

#LI-Remote