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:

• Leading a team of Data Scientists and helping them set goals, collaborate, and scale, and operationally manage ad-hoc requests
• Providing mentorship to team members through feedback, coaching, and hands-on technical guidance, focusing on their long-term growth
• Partnering with senior leaders including Product & Engineering to ensure data-driven decisions across the organization by applying the appropriate data science & analytics approaches where they will have a material impact
• Thinking strategically to optimize the key components of the Signifyd Commerce Protection Platform
• Collaborating with engineering teams to continuously strengthen our machine learning pipeline
• Collaborating with Customer Success and Risk Intelligence to optimize decisioning performance
• Researching real-time emerging fraud patterns with our Risk Intelligence team
• Building production machine learning models that identify fraud
• Writing production and offline analytical code in Python 
• Working with distributed data pipelines

Past experience you’ll need:

• A degree in computer science or a comparable analytical field
• 2+ years of experience in people management with experience building teams and growing talent
• At least 4 years of post-undergrad work experience required
• Experience leading projects that depend on the contributions of others in multiple teams
• 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

Experience we love to see:

• Experience managing remote teams
• Previous work in fraud, payments, or e-commerce
• Data analysis in a distributed environment
• Passion for writing well-tested production-grade code

#LI-Remote

Benefits in our US offices:

• Discretionary Time Off Policy (Unlimited!)
• Mental wellbeing resources
• 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