About the team
Our team researches and develops machine learning models and prototype systems that help make the Internet a safer place. We serve customers across multiple verticals such as online commerce, delivery service, finance, and travel sites etc. Our customers spread around the globe in both developed and developing countries. Our technology helps protect their users from ever-evolving online scams, payment fraud, abusive content, and account takeover, etc. We are a forward-thinking team constantly challenging ourselves and the status quo to push the boundary of machine learning and data science across multiple product offerings at SIFT and collaborate with product engineering teams to deliver concrete customer value.
We take pride in our work, not ourselves. Open and constructive feedback is valued and often required to ensure rigor in our work. We love learning, hacking, and sharing our findings. We believe that machine learning is THE way to empower internet-scale businesses to thrive.
What you'll do
What would make you a strong fit:
A little about us:
Sift is the leading innovator in Digital Trust & Safety. Hundreds of disruptive, forward-thinking companies like Airbnb, Zillow, and Twitter trust Sift to deliver outstanding customer experience while preventing fraud and abuse.
The Sift engine powers Digital Trust & Safety by helping companies stop fraud before it happens. But it’s not just another anti-fraud platform: Sift enables businesses to tailor experiences to each customer according to the risk they pose. That means fraudsters experience friction, but honest users do not. By drawing on insights from our global network of customers, Sift allows businesses to scale, win, and thrive in the digital era.
Benefits and Perks:
Sift is an equal opportunity employer. We make better decisions as a business when we can harness diversity in thought, experience, data, and background. Sift is working toward building a team that represents the worldwide customers that we serve, inclusive of people from all walks of life who can bring their full selves to work every day, so we can Win as One Team.
This document provides transparency around the way in which Sift handles personal data of job applicants: https://sift.com/recruitment-privacy