LeapYear's secure data platform is deployed by some of the largest enterprises in the world across finance, healthcare, and technology.
Our technology ensures differential privacy, a widely recognized standard of data privacy that enables all data - including sensitive information - to be utilized for analytics, while providing mathematically proven privacy protection.
Our Algorithms team is at the forefront of our efforts to apply differential privacy to real-world problems. We take exciting, cutting-edge ideas from the research community and develop novel implementations that enable our customers and partners to do incredible things with sensitive data.
We work in Python, Haskell, and Scala to develop these algorithms, closely partnered with domain experts as well as the rest of the engineering organization. In the past, we’ve produced everything from Python-based experiments, to safety and performance-critical distributed implementations in Haskell and Scala/Spark.
Our ideal team-mate is someone who loves learning and teaching. We’re challenged to stay current with both the latest research in privacy-preserving technologies, as well as thinking about how to apply and explain those ideas effectively to the complicated worlds of our users and customers.