David Rozzi
Vice President, Technology Projects, New York Post (News Corp)
- Role
- Vice President, Technology Projects at New York Post
- Location
- Brooklyn, NY, US
- LinkedIn followers
- 500 followers
About David Rozzi
I architect and oversee development for the Customer Identity & Behavioral Graph, the Data Architecture / Lakehouse that supports it, and the Customer Data Platform. I work with the business to develop technical solutions and personalization opportunities to drive revenue and engagement goals via use cases for personalized customer journeys and targeting across all products and platforms.
Experience
Vice President, Technology Projects
Jul 2021 — Present · New York, NY, US
I have oversight and architectural responsibilities for the Identity & Behavioral Graph, the CDP, and the Lakehouse that supports these. This includes:Identity- The customer identity / behavioral graph for known and anonymous users across all products- A rules engine for customer intention, preference and life phase cohorts- Real-time integrations between the identity graph and network advertising partners to enhance user profiles in the openmarket / DMP to increase CPMs- Demographically augmented user profiles via identity partners and clean rooms using unique identifiers, HEMs, MAIDS, other signals- First-party tag and other identifying signals for all products, for both known and anonymous users, accounting for cookie deprecation, ITP rules and privacyPersonalization, Targeting & Activation- The Customer Data Platform (Building audiences & journeys, integrating new data channels & streams, ensuring identity, building activation channels)- Working with business owners (Marketing, Editorial, Ecommerce, Advertising, Data Science) to define use cases to drive and build real-time and recurring activations, targeting and user journeys across multiple touchpoints and platformsArtificial Intelligence and Machine Learning- Assisting with the implementation of AI models to power content recommendations, personalization and data analysis- Machine Learning for propensity and affinity scoring to drive audiences and targeting via the CDPData Lakehouse- ETL and data architecture; collecting, ingesting and transforming user data (behavioral and profile) from all channels, products and platforms for use in the identity graph, CDP, AI models and data analysis—ensuring low-cost materialization, compute, query and storage architecture
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