The Data Science team builds production machine learning models that are core to Signifyd's product, helping businesses minimize fraud exposure and grow sales. Our product improves e-commerce experiences by reducing order declines and making account hijacking less profitable for criminals.
The team owns the decision engine end-to-end, from research to online performance and risk management. We value collaboration, team ownership, and continuous learning through peer reviews, group studies, and knowledge sharing via demos, write-ups, and cross-team projects.
Signifyd has a strong remote culture, with many remote contributors and leaders, and we continuously seek to improve this culture.
We seek someone who embodies our company values:
* Curious and Hungry: Willing to research and experiment hands-on
* Tenacious: Persistent in creating solutions
* Customer Passion: Focused on staying ahead of fraudsters
* Design for Scale: Able to build scalable fraud protection solutions
* Agile: Adaptable between research and real-time analysis
* Roll Up Your Sleeves: Collaborate closely and learn from others
Impact:
* Building ML models for fraud detection
* Writing production and analytical Python code
* Working with distributed data pipelines
* Communicating complex ideas effectively
* Collaborating with engineering teams to enhance our ML platform
Requirements:
* Bachelor's in CS, math, economics, or related field or equivalent experience
* 5+ years of experience
* Strong statistical analysis skills
* Experience designing experiments and data collection
* Proficiency in Python coding and code review
* Practical SQL knowledge
* Familiarity with Linux command line
* Availability for on-call shifts, approximately six weekends a year
Bonus points if you have:
* Advanced degree (Master's or PhD)
* Experience in fraud, risk, payments, or e-commerce
* Experience working with GTM teams
* Distributed data analysis experience
* Passion for production-grade, well-tested code
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