Member privacy is a priority at LinkedIn and a key consideration in product design. We aim to protect member privacy by using innovative privacy engineering techniques such as differential privacy to provide valuable insights to members and policy makers. The differential privacy team at LinkedIn has developed new algorithms that work with existing real time data analytics systems, allowing us to develop systems at scale while protecting member privacy. This talk will cover several deployments of LinkedIn products that incorporate differential privacy.