Data Analysis, Data science techniques, Ecommerce, Effective communication skills, English Proficiency, Linux Operating system, Machine learning techniques, Python Programming, SQL, Statistics
The Data Science team builds production machine learning models that are the core of Signifyd's product.
Our product helps businesses of all sizes minimize their fraud exposure and grow their sales. This translates into improved e-commerce shopping experience for individuals, by reducing the number of orders that are incorrectly declined, and by making account hijacking less profitable for criminals.
The data science team has end-to-end ownership of our decision 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 grow our skills through peer reviews, group studies, and frequent knowledge sharing to deepen our ML and stats understanding. This is done through live demos, write-ups, and special cross-team projects.
The Data Science and Engineering teams 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 strive to iteratively improve our remote culture.
We are looking for someone who embodies our company values:
How you’ll have an impact:
Requirements:
Bonus points if you have
Signifyd provides an end-to-end Commerce Protection Platform that leverages its Commerce Network to maximize conversion, automate customer experience and eliminate fraud and consumer abuse for retailers. Signifyd’s customers appear on the Fortune 1000 and Digital Commerce 360 Top 1000 lists. Digital Commerce 360 also named Signifyd the leading provider of payment security and fraud prevention for the Top 1000 Retailers for 2022. Signifyd is headq