Product Manager - Podcast Recommendation Technology
A full time position at Spotify, New York NY, USA
Posted: January 4, 2021
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
Spotify is building the world’s most personalized audio service. We’re looking for a Product Manager to join our Personalization Platform team to accelerate our efforts to understand podcast listening behavior and taste, build core podcast recommendation technology, and consistently match user interests with relevant podcast content. You’ll work with stakeholders, internal customer teams, user researchers and data scientists to build a roadmap and strategy for the core podcast recommendation technology needed to fuel a best in class podcast discovery experience. You will work with a team of crack engineers to build data products and machine learning models that represent user taste and interests and the vast and growing Spotify podcast content catalog, and collaborate with feature teams across the product to build compelling user podcast experiences. Products you build will enable personalized podcast experiences for users across the Spotify ecosystem.
The Personalization Platform team builds models, tools, and data products that represent users, their habits and tastes and their relationship to content and creators, as well as the APIs to serve that intelligence. We work with internal teams to deliver the building blocks of intelligence for all personalized features across the Spotify experience.
What You'll Do
- Engage with product, analytics, and user research teams to identify podcast recommendation needs for users across the globe
- Explore new opportunities and use cases for bringing podcast recommendations to users in the Spotify experience
- Work with the engineering team to articulate the vision and set the roadmap for core recommendation technology for podcasts
- Define requirements for and work with engineering to design data products and machine learning models required for broad podcast recommendation needs
- Define, monitor, and analyze business and quality metrics for data products and machine learning models, and feed learnings back into the development process
- Build relationships with stakeholders across the organization understand and prioritize foundational needs across use cases and short and long term horizons
- Work closely with engineers to allow for fast development, evolution, and innovation of core data and machine learning products and tooling
- Ensure quality of data products and machine learning models, including timeliness, performance, and accuracy
- Make sure that your team is strong and healthy – including capabilities, happiness, resilience and growth
- (Eventually) Work from our office in New York City
Who You Are
- You have at least 3 years of product management experience, ideally with experience in the areas of AI or ML products and are adept at knowing when and how to use those technologies to solve product problems
- You have worked in a product role for an internal platform or B2B environment, and are skilled at understanding the needs of and serving internal customers or teams or other businesses
- You have demonstrated the ability to translate strong user empathy and understanding of pain points and needs into something tangible that users or customers love
- You have experience working with engineers to set requirements for data products and/or predictive algorithms, and are passionate about building and being part of high performing teams
- You have experience working in an Agile environment
- You are experienced in setting and executing on a product backlog, balancing innovation, maintenance and support
- You are experienced at creating and communicating a narrative about the value of data, models, and platforms to unlock business value and transform end user experiences
Get more details
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