Data Scientist

Signifyd leads the world in bringing the insights, innovation and compassion required to foster fearless commerce in a time of increasing digital threats. Working with some of the industry’s most recognizable retailers and brands, we are focused on using technology to enhance customer lifetime value and protect enterprises from fraud so they can focus on growing their business. 

We process billions in ecommerce transactions annually through our Commerce Network of thousands of merchants selling in more than 100 countries. We focus every day on harnessing machine learning and artificial intelligence in more powerful ways to maximize our customers’ revenue and their security. None of that happens without the right people.

Our team’s strength is in its diversity and its acceptance of new ideas and new ways to look at old challenges. We are dedicated disruptors designing a new world of commerce at scale. We know humans are not one-dimensional and we celebrate the uniqueness each individual brings to the problems we solve and the culture we create.

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 skill sets through peer review of experiments and code, group paper study to deepen our ML and stats understanding, and frequent knowledge-sharing via 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 as well as team leads. The challenges of working remotely aren't new to us and we have a track record of iterative improvements to our remote culture.

How you’ll have an impact:

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

Past experience you’ll need:

• A degree in computer science or a comparable analytical field
• At least 2-3 years of post-undergrad work experience required
• Using visualizations to communicate analytical results to stakeholders 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 collecting 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 

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