the truth is out there!
1,045 karma · joined April 30, 2010
Past: University of Washington '06 Computer Engineering and then Zillow, Optify, and BuzzLabs.
We are a hyper-growth Series C company based in San Francisco. We’re in the business of squashing fraud and other malicious activity for the world’s largest web and mobile businesses. Our next-generation platform is built on proprietary machine learning technology that learns in real time from live activity taking place on the sites and apps of our global network of customers. By integrating our modern REST APIs and automation workflows, our customers not only eliminate risk but also increase revenue and conversion rates through user experience optimization.
Open Roles:
- Data Scientist
- Senior Backend Engineer
- Senior Full Stack Engineer
- Senior Machine Learning Engineer
- Senior Site Reliability Engineer
- Software Mobile SDK Engineer
We’re hiring in our San Francisco and Seattle office and we would love for you to join the team! If interested please visit our careers page and apply https://siftscience.com/careers.
More Info: https://engineering.siftscience.com/ Questions? E-mail Recruiting@siftscience.com
Unfortunately, evil exists. Fortunately, we're here to stop it! Fraud and abuse plague online businesses of all types, from marketplaces to payment processors, social networks to e-commerce stores. As the internet's trust layer, Sift Science's mission is simple yet powerful: make these online experiences faster, smoother, and safer – using the smartest technology around.
Sift Science is hiring for Backend Engineers, SREs, Full Stack Generalists and Mobile SDK Eng.
Curious about what we're working on? Visit us at engineering.siftscience.com to learn more.
Apply at www.siftscience.com/careers
Great job, Wallarm!
Unfortunately, evil exists. Fortunately, we're here to stop it! Fraud and abuse plague online businesses of all types, from marketplaces to payment processors, social networks to e-commerce stores. As the internet's trust layer, Sift Science's mission is simple yet powerful: make these online experiences faster, smoother, and safer – using the smartest technology around.
We just raised $30M in Series C funding from Insight Ventures -- join us in making the internet a better place!
We are hiring for:
-Senior Backend Engineers
-Senior Site Reliability Engineers
-Senior Full Stack Engineers
-Sales people
-Business Operations
-Web Developers
Email: Recruiting@siftscience.com
Sift Science (YCS11) is hiring Machine Learning Engineers, Console Engineers, Engineering Managers, DevOps Engineers and more!
Full-time. Sift Science uses real-time machine learning to fight online fraud. It's a problem that cost U.S. merchants > $12B last year with 70% being a result of organized crime. We are currently seeking ML engineers to join our team to work on our diverse and exponentially growing dataset to employ large-scale, online machine learning and model millions of unique features. Sift is a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs or ping us at recruiting@siftscience.com for more information :)
Sift Science uses real-time machine learning to prevent and predict online fraud. We are a lean group of driven and collaborative people passionate about bringing machine learning into the real world. Do you despise evil? Believe fraud must be eradicated from the internet? If so, Sift Science must be for you.
We are hiring for engineers (front-end, machine learning and everything in between), sales, marketing and business experts.
Visit jobs.siftscience.com or reach out directly to lynda@siftscience.com for details/questions.
Sift on!
Even if you don't use us, we published some articles to help merchants new to dealing with fraud: * https://siftscience.com/sift-edu/fraud-basics * https://siftscience.com/sift-edu/prevent-fraud
Full-time, Onsite. Sift Science uses real-time machine learning to fight online fraud. It's a problem that cost U.S. merchants > $12B last year with 70% being a result of organized crime. We are currently seeking ML engineers to join our team to work on our diverse and exponentially growing dataset to employ large-scale, online machine learning and model millions of unique features. Sift is a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs or ping us at recruiting@siftscience.com for more information :)
Sift Science uses real-time machine learning to fight online fraud. It's a problem that cost U.S. merchants > $12B last year with 70% being a result of organized crime. We are currently seeking ML engineers to join our team to work on our diverse and exponentially growing dataset to employ large-scale, online machine learning and model millions of unique features. Sift is a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs or ping us at jobs@siftscience.com for more information :)
Jason here, op and CEO of Sift Science. You have a point, but do keep in mind that the TV is going to a bad customer -- one that won't reward Best Buy with repeat business (perhaps just more fraud) and won't spread positive word of mouth (except to let other fraudsters know that Best Buy is a great fraud target). So there is some "lose" in shipping the TV to a bad customer, different from shipping it to a good customer. Does that make sense?
but, rules are rather easy for fraudsters to circumvent, and they require merchants to play whack-a-mole. with today's technologies, it's easier than ever to analyze massive amounts of data, and we believe that machine learning can go a really long way in detecting fraud.
does that make sense? happy to discuss further, and we'd be happy to put you in touch with our customers if you'd like to hear more about our results.
I've contacted the reporter to try and clear this up.
Sift Science (http://siftscience.com) uses large-scale machine learning to fight online fraud. It's a problem that cost U.S. merchants > $10B last year, and 70% of it is organized crime. Attacks have rapidly evolved in breadth and depth, but current rule-based systems don't scale. We're looking for engineers of all flavors -- distributed systems, web development, data visualization, site reliability, and of course, machine learning. We're a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs We're also looking for integration engineers, technical writers, a head of marketing, a head of integration engineering, an office manager, and a finance person. jobs+hn at siftscience dot com
Sift Science uses large-scale, real time machine learning to fight online fraud. It's a problem that cost U.S. merchants > $10B last year, and 70% of it is organized crime. Attacks have rapidly evolved in breadth and depth, but current rule-based systems don't scale.
We're looking for engineers of all flavors -- distributed systems, web development, data visualization, and of course, machine learning. We're a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs We're also looking for account managers, solution engineers, sales, and a product marketing leader. Feel free to email me personally - jason at siftscience dot com
This means that you're left to defend yourself. Typically, you'll start implementing some basic verification and rules in your code base. For example, "if num_credit_cards_per_destination > 5; flag_as_suspicious()". But, it's tough to be accurate with this approach, so you'll want to manually review activity flagged by rules, so that you don't insult your good customers. As your business grows, it's more challenging to scale these fraud detection rules and manual review operations. While adding more verification helps, it does negatively impact the experience for innocent customers. It's a delicate balance.
I wish I had better news. In some sense, seeing fraud means that you're on the map. Unfortunately that means you'll only attract more and more attention as your business grows. I'm happy to be a resource, even if we don't work together - jason at siftscience dot com.
Sift Science (http://siftscience.com) uses large-scale machine learning to fight online fraud. It's a problem that cost U.S. merchants > $10B last year, and 70% of it is organized crime. Attacks have rapidly evolved in breadth and depth, but current rule-based systems don't scale. We're looking for engineers of all flavors -- distributed systems, web development, data visualization, and of course, machine learning. We're a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs We're also looking for account managers, integration engineers, and someone to lead our B2B marketing efforts. jobs+hn@siftscience.com
Sift Science (http://siftscience.com) uses large-scale machine learning to fight online fraud. It's a problem that cost U.S. merchants > $10B last year, and 70% of it is organized crime. Attacks have rapidly evolved in breadth and depth, but current rule-based systems don't scale. We're looking for engineers of all flavors -- distributed systems, web development, data visualization, and of course, machine learning. We're a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs We're also looking for account managers, integration engineers, and someone to lead our B2B marketing efforts. Feel free to email me personally - jason at siftscience dot com
Sift Science (http://siftscience.com) uses large-scale machine learning to fight online fraud. It's a problem that cost U.S. merchants > $10B last year, and 70% of it is organized crime. Attacks have rapidly evolved in breadth and depth, but current rule-based systems don't scale. We're looking for engineers of all flavors -- distributed systems, web development, data visualization, and of course, machine learning. We're a tight-knit team that likes board games, yummy food, and solving challenging technical problems. Check out https://siftscience.com/jobs We're also looking for our first product manager, account managers, integration engineers, and someone to lead our B2B marketing efforts.
Feel free to email me personally - jason at siftscience dot com