Description:

The Data Science team at Signifyd builds models that power the fraud detection engine.
The machine learning pipeline is designed to stay ahead of fraudsters and their evolving tactics.
Research and experiments conducted by the team develop into new products that enhance the merchant payments experience.
Data scientists are expected to be hands-on, carrying solutions from brainstorming to experimentation and deployment.
The team is diverse, with members from various backgrounds including academia, engineering, and different company sizes, all sharing a curiosity and collaborative spirit.
The role requires embodying company values such as being curious and hungry, tenacious, customer passionate, designing for scale, agile, and willing to roll up sleeves to partner closely with others.
Responsibilities include building production machine learning models to identify fraud, designing new algorithms for the Signifyd Commerce Protection Platform, writing production and offline analytical code in Python and Java, researching real-time emerging fraud patterns, working with distributed data pipelines, communicating complex ideas effectively, collaborating with engineering teams, and mentoring team members.

Requirements:

A Bachelor's degree in computer science, applied mathematics, economics, or an analytical field is required.
An advanced degree (M.S. or Ph.D) in an analytical field is a plus.
At least 3+ years of experience in a relevant field is necessary.
Hands-on statistical analysis experience with a solid fundamental understanding is required.
Experience in designing experiments and collecting data is essential.
Proficiency in writing code and reviewing others’ code in a shared codebase, preferably in Python and Java, is required.
Practical knowledge of SQL is necessary.
Familiarity with the Linux command line is required.
Fluency in English is mandatory.

The company provides an inclusive interview experience and is willing to offer reasonable accommodations for candidates with disabilities during the hiring process.
Employees have the opportunity to work in a collaborative and diverse environment.
The role offers the chance to impact fraud detection and improve merchant payments experience significantly.
There are opportunities for professional growth and mentorship within the team.