Location: United States
Cap-Exempt H-1B Position — No lottery required
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. **The Team You Will Join** Our team uses data for the consumer product security in two ways: 1) provide insights into effectiveness of security measures across products, and 2) build intelligence to address fraud in scale. Examples of fraud we deal with include account compromise, piracy, and DDoS. We achieve our goals through both technical work on the team and cross-functional partnerships. We are looking for an analytics engineer to join our team to drive security metrics as well as data solutions for detection and prevention across the fraud landscape. If you've used Netflix, you've been protected by systems that our team built. We collaborate closely with Product, engineering, Data teams, as we believe security is a team sport. This blog post is a great way to learn about our work. **What You Will Work On** As a Security Analytics Engineer, you will drive insights and discovery of fraud in our ecosystem by understanding our infrastructure, and product, identifying high risk areas, and driving changes to our anomaly detection and product experiences. You will leverage your security and fraud prevention expertise to analyze patterns, identify new signals, and recommend adjustments based on impact to our customers and Netflix. - Develop data-driven insights to influence our device & product security strategy, including identifying new signals for anomaly detection - Compile and track anomalous request patterns and identify potential mitigations - Design and champion data‑driven security enhancements that strengthen our devices and safeguard our rich content catalog. - Analyze error logs to quant