Mission: Our mission is to power trust online. We're using machine learning to fight fraud and abuse, protecting 6,000+ sites and apps from fraudsters, spammers, and scammers.
Sift Science is a hyper-growth Series D company that facilitates the largest trust network of online businesses and consumers on the internet.
The Sift Science Trust Platform uses real-time machine learning to accurately predict which users businesses can trust, and which ones they can’t. The upshot? Consumers know which companies they can entrust with their personal and financial information. And businesses can customize each user's experience based on their trust score – which leads to more revenue, higher conversion rates, and less fraud and abuse.
Come do your best work, with the brightest fraud fighters in the industry - Sift Careers
We’ve got runners, cyclists, yogis, and even a Sift Hiking Club. We also participate in kickball and basketball leagues. If you’re more the indoor type, join our board and video game enthusiasts. We host movie nights and have clubs for cheese, coffee, wine, and whiskey.
We invested in a Talent Development function before any of our peers. This team is responsible for the strategy and execution of our learning culture, including manager effectiveness feedback and training, a peer feedback process, Radical Candor training, individual coaching, and just-in-time learning content from cutting-edge providers.
Whether it’s hosting middle schoolers, a Women in Tech event, or a discussion about machine learning, Sifties are always finding a way to give back to the community. Sift Cares is an initiative which organizes a variety of events throughout the year, allowing Sifties to get involved with a myriad of worthy community causes through volunteering, events, and knowledge sharing.
We’re solving an important problem. Fraud and abuse plague online businesses of all types, from marketplaces to payment processors, social networks to e-commerce stores. In fighting fraud we’re making online experiences faster, smoother, and safer – using the smartest technology (and people!) around. Very rarely do you find the opportunity to work with a company that leverages cutting-edge technology while solving critical global problems
The 30+ members of our engineering team are building:
We're open for business in Seattle!
Easy integration? Don't take our word for it!
Watch a brief excerpt from Michael Widell's talk at the Nordic API conference, where he uses Sift Science as an example of a product that is easy-to-integrate and has open, accessible, and easy to understand API documentation.
I have been working at Sift Science full-time (Less than a year)
I've followed Sift's progression from early stage startup to high growth company. From the outside, I was impressed by the company's tech and their ability to solve complex fraud problems using Machine Learning. Now as an employee, I realize that what really sets this company apart is the culture and its people.
Sift has a values driven culture that is actively evolving as the company scales. More importantly, Sift is filled from top to bottom with smart, thoughtful, collaborative people. When dealing with challenges in pressure situations, Sifties are focused on attacking the problem while supporting each other. This is enabled by a leadership team that consistently does right by its employees.
It's this fabric of culture and people that make me excited about the professional and personal growth opportunities at Sift for many years to come.
There are lots of challenges to operating effectively and smoothly within a high growth business forging into new markets. Sift moves quickly and sometimes has to make decisions in the absence of (reliable) data. I think the bumps in the road are very typical for a tech business at this stage.
Advice to Management
Our company Values are powerful. Reinforce them over and over. Especially as we scale, new people need to be ingrained within the culture and reminded of how we do business.
I applied through other source. The process took a week. I interviewed at Sift Science in October 2014.
I applied through Piazza Careers and was called only a week after. The first round was a basic programming round. The questions asked were 1) Level order traversal of a tree 2) Difference between a shallow vs deep copy