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 

#LI-Remote

Benefits in the USA:

• 4-day workweek
• Discretionary Time Off Policy (Unlimited!)
• Talkspace Online Therapy Membership
• Dedicated learning budget through Learnerbly
• 401K Match
• Stock Options
• Annual Performance Bonus or Commissions
• Paid Parental Leave (12 weeks)
• Health Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Account (FSA)
• Short Term and Long Term Disability Insurance
• Life Insurance
• Company Social Events
• Signifyd Swag