Principal Data Scientist

NBCUniversal, the global media company that brought you some of the world’s most iconic television and film franchises, including: The Tonight Show, Saturday Night Live, Keeping Up With The Kardashians, The Real Housewives, Mr. Robot, The Voice, This Is Us, The Fast & The Furious, Jurassic Park, Minions, and more is looking for a Principal Data Scientist to lead a team working on personalization at Peacock.  Are you a fan of machine learning solutions, reinforcement learning, deep learning, and foundation models? Do you want to be a part of the team that builds an advanced recommender engine, active leaning platforms, and personalized solutions for marketing and advertisement? Join the world-class international team of smart and hungry professionals who are working at the cutting edge of technology and science at the epicenter of content, technology and culture. Position Overview: As part of the Media Group Decision Sciences team, the Principal Data Scientist will be responsible for creating machine learning solutions for NBCU’s video streaming service including but not limited to, content recommendations and product experience personalization. In this role specifically, the Principal Data Scientist (Deep Learning) will lead algorithmic solution design, rapid prototyping, and technical review for the ML/AI models underlying personalized user experiences and content promotion. They will be a key point of contact for cross-functional architects and software developers as they integrate personalized data products and capabilities across our suite of global and domestic products. They will work with a dynamic cohort of high caliber individuals across Product, Technology, Marketing, Content Discovery, Editorial, and more to build a state-of-the-art real-time video streaming service Responsibilities include, but are not limited to: Be a resident expert in recommendation systems design and implementation. Lead the team in the development of a recommendation system modeling and experimentation framework. Work with business stakeholders to define priorities, approaches and business requirements for analytical solutions. Manage multiple priorities across business verticals and machine learning lifecycle projects. Laise with engineering teams to define data science driven requirements and solutions for major initiatives and opportunities of the streaming service functionality. Drive innovation of the statistical and machine learning methodologies and tools used by the team. Lead improvements in machine learning lifecycle infrastructure. Drive a data science culture that inspires and motivates the team to succeed.