- Natural Language Processing
At Pandora, we're a unique collection of engineers, musicians, designers, marketers, and world-class sellers with a common goal: to enrich lives by delivering effortless personalized music enjoyment and discovery. People—the listeners, the artists, and our employees—are at the center of our mission and everything we do. Actually, employees at Pandora are a lot like the service itself: bright, eclectic, and innovative. Collaboration is the foundation of our workforce, and we’re looking for smart individuals who are self-motivated and passionate to join us. Be a part of the engine that creates the soundtrack to life. Discover your future at Pandora!
Our Intern program offers two 12-week sessions. Please let us know which session you would like to participate in.
June 3rd through August 23rd
June 17th through September 6th
The Content Science team builds data science products and services for content creators such as artists, curators, and programmers, to create the best-in-class curated music catalog and programs, promote music and concerts through our Artist Marketing Platform, and build personalized listening experiences to introduce podcasts to millions of Pandora listeners. As a Content Science intern, you will have the opportunity to contribute to a broad set of problems ranging from enhancing our content understanding for music and podcasts to building recommendation algorithms to power our next generation of podcast personalization services. Successful candidates will have expertise in machine learning and statistics, solid programming skills, outstanding communication skills, and ability to work in a team with a diverse skill set.
To land this gig, you will need:
Pursuing a PhD degree in a quantitative field (e.g., Computer Science, Machine Learning, Natural Language Processing)
Demonstrated expertise in machine learning and/or artificial intelligence
Proficiency with Python or R
Familiarity with SQL or Hive (or proprietary equivalent)
Bonus points if:
Expertise in Natural Language Processing or Natural Language Understanding
Recommendation System experience
Experience with one or more of the following: topic classification, topic detection, entity resolution, semantic search, knowledge graphs, narrative structure understanding, machine reading, and text mining
Experience with the Hadoop technology stack
Experience with Spark and Scala
Experience with the design and execution of large-scale quantitative analyses