Senior Marketing Data Scientist, Media Subscriptions

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 & 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.
We are currently seeking an experienced data scientist who is passionate about motivating change at the intersection of data and marketing. As a Marketing Data Scientist for Apple Services, you will help drive growth in media services and evolve our marketing programs through attribution, causal inference, A/B testing, and LTV prediction modeling. Your work will directly influence Services strategy for driving engagement and revenue growth.

As a key member of our diverse and dynamic organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to customer privacy that will frequently require innovative approaches. You'll work collaboratively with partners across Business, Marketing, Product, and Engineering daily to deliver material customer and business value.
<h3>Minimum Qualifications</h3>5+ years of experience extracting business insights from large datasets, specifically employing programming languages like Python and SQL
Demonstrated ability in a Data Scientist or Data Analyst role, preferably for a digital media, MarTech, digital subscription business, or technology business
Excellent communication and presentation skills with meticulous attention to detail with the ability to communicate effectively between marketing, business and analytics teams
Experience with standard marketing data science analysis to include experimental design, linear regression, clustering, survival, and quasi-causal analysis, with solid experience measuring both paid and non-paid campaigns
Curious business mindset with an ability to condense complex concepts and analysis into clear and concise takeaways that drive action
Bachelors degree in Computer Science, Economics, Engineering, Mathematics, Data Science, Statistics or equivalent professional experience
<h3>Preferred Qualifications</h3>Experience in and/or passion for the media and entertainment industry
Experience analyzing the performance of subscription businesses and familiarity with subscription lifecycle metrics
Skilled at measuring advertising value through causal inference techniques
Advanced degree in a related field preferred