Staff Product Manager, Personalization - Digital
The Staff Product Manager, Personalization is responsible for driving CNN's personalization strategy and execution. You are someone who's passionate about defining and building end to end personalization and recommendation experiences. You think in the domain of Machine Learning and AI and are equally comfortable with design thinking to tie the best user experience and ML models together. You enjoy working with product designers, data scientists, researchers, engineering, and editorial teams to deliver the best personalized experience that balance user needs and business goals.
• Drive CNN digital's personalization and search strategy across multiple platforms (apps, web, and TV) with multiple content types (articles, videos, and podcasts)
• Lead a full stack personalization product team of designers, researchers, data scientists, engineers, and editors to discover and deliver best-in-class personalized news experiences, from designing UX to developing Machine learning models to scaling APIs
• Partner with data scientists and researchers to identify user needs and pain points
• Partner with engineers to research, develop and iterate on Machine Learning models
• Build a roadmap and execution strategies to ensure successful product delivery
• Define key metrics and quarterly OKRs to measure the success of experimentations and features
• Partner with product teams across the company to integrate ML models and experiences in other product portfolios
• At least 3 years of product management experience, ideally with consumer facing product experience with Machine Learning and AI components
• Passionate about algorithms and personalization products and understand the opportunities and limitations of Machine Learning and AI
• Experience in working with a full stack team and have demonstrated clear impact with products shipped
• Comfortable diving into data and metrics and have experience working with data scientists to define and measure KPIs. SQL skill is preferred
• Experience in designing, implementing, and running online experimentations.
• Strong presentation and communication skills in delivering strategies to cross-functional leadership teams and gaining support
Jobcode: Reference SBJ-r0nmzm-3-230-144-31-42 in your application.