About the Role
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 Services Data Science & Analytics organization is passionate about developing discerning insights and AIML solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy.
We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help optimize marketing channels, via observational testing frameworks, counterfactual modeling, and lifetime value estimation. As a key member of our diverse organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to privacy that will frequently require novel approaches. You'll work alongside partners across Business, Marketing, Product, Finance, and Engineering daily to deliver material customer and business value.
Responsibilities
- Push the boundaries of how Causal Inference and AIML can be leveraged to better serve customers
- Design, develop, and deploy cutting-edge Causal Inference solutions that directly impact products and provide a granular understanding of key marketing effectiveness
- Define the technical vision, strategy, and execution roadmap for AIML initiatives
- Ensure delivery of high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges
- Drive a vibrant culture of innovation, continuous learning, and collaborative problem-solving
Minimum Qualifications
- Master's degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field
- 3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist
- Familiarity with a broad range of quasi-experimental Causal Inference techniques such as diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matching
- Hands-on experience building Marketing Mix models and validation through Matched Market testing
- Solid understanding of AIML technologies including Generative AI
- Proven track record of successfully delivering complex projects from start to finish
- Proficiency in programming languages such as Python, R, SQL, Java, or C++
- Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices
- Excellent communication, collaboration, and presentation skills with meticulous attention to detail
Preferred Qualifications
- PhD in related field
- Hands-on experience leveraging Generative AI to improve productivity and generate new insights
- Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action
About Apple
Apple designs, manufactures, and markets smartphones, personal computers, tablets, wearables, and accessories worldwide. The company also provides software, digital services, and subscription platforms including the App Store, Apple Music, Apple TV+, iCloud, and Apple Pay.
Interested in this role?
Apply now to join Apple.