Video Content Data Scientist

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps, award-winning shows and movies, immersive music in spatial audio, world-class workouts and meditations, super fun games and more!

The Apple Media Products Data Science u0026 Analytics organization is passionate about developing discerning insights and machine learning solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy.

Our team is looking for a data scientist to help support the Video business teams (including TV+) with insights on content performance, strategy, and customer experience in the TV app.

As a key member of our diverse and multifaceted organization, we have the rare and exciting opportunity to work with datasets of unique magnitude, richness, and dedication to customer privacy that will frequently require innovative approaches.

We work collaboratively with partners across Business, Marketing, Product and Engineering daily to deliver material customer and business value.

Experience in media or entertainment industry.

Passion for film, television, and/or Sports domains.

Hands-on experience with app-based engagement and clickstream data.

Experience with distributed computing frameworks like Spark.

Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, or related field.

4 years experience extracting insights from large datasets, specifically employing programming languages like Python and SQL.

4 years experience employing statistical methods to tackle business problems related to classification, segmentation, and forecasting.

Demonstrated ability to apply data science techniques to find answers to ambiguous real-world questions in a changing environment and communicate them to stakeholders.

Comfort working cross-functionally across multiple teams, including both technical and non-technical partners.

Strong interpersonal and communication skills.