The Data Science team builds production machine learning models that are the core of Signifyd's product.

We help businesses of all sizes minimize their fraud exposure and grow their sales. We also improve the e-commerce shopping experience for individuals by reducing the number of folks' orders that are incorrectly declined and by making account hijacking less profitable for criminals.

The team has end-to-end ownership of our decisioning 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 skills 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.

The Data Science and Engineering team at Signifyd have always had a strong contingent of remote folks, individual contributors and team leads. The challenges of working remotely aren't new to us and we have experienced iterative improvements to our remote culture.

How you'll have an impact:

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

Requirements:

• A degree in computer science or a comparable analytical field, or equivalent practical experience
• 2+ years of relevant work experience required
• Using visualizations to communicate analytical results to members outside your team
• Hands-on statistical analysis with a solid fundamental understanding
• Writing code and reviewing others’ in a shared codebase, preferably in Python
• Practical SQL knowledge
• Designing experiments and collect data
• Familiarity with the Linux command line
• This role has on-call shifts, as part of our weekend rotation, Fri/Sat/Sun. While the number of shifts is subject to change, currently it works out to about six weekends a year.

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

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