Our vision is to bring more innovation, efficiency, and equality of opportunity to the world by creating an open financial system. Our first step on that journey is making digital currency accessible and approachable for everyone.
Two principles guide our efforts. First, be the most trusted company in our domain. Second, create user-focused products that are easier and more delightful to use than any alternative. Those principles guide every decision across the company from design through engineering, from operations through risk and security.
Digital currency is fungible, instantly transferable and irreversible. This attracts sophisticated bad-actors. First, fraudsters use stolen bank accounts or cards to try to buy digital currency and immediately move it to a private wallet that's only in their control. Second, hackers target Coinbase user accounts in an attempt to drain their balance. We've been able to stay ahead of bad actors via a combination of machine learning, data-driven rules engines and anomaly detection. To learn more, check out slides , video , or this podcast for a talk on this topic.
Solve one of the hardest payment fraud problems in the world
Build and scale data services (machine learnt risk scoring, rules engines, anomaly detection)
Gather data signals that identify fraudulent activity via integrations with payment and identity vendors
Exhibit our core cultural values: add positive energy, communicate clearly, be curious, and be a builder.
4+ years of engineering experience in fighting badness (fake accounts, spam, account takeovers, payment fraud)
Experience with building and scaling at least 1 data service (e.g. risk scoring, rules engines, anomaly detection)
Experience working with large and messy data sets (eg web logs, network data, images) and deriving meaning out of it.
Experience with Python, SQL, and a JVM-based language. Bonus points for Kotlin.