Senior Product Data Scientist in Causal Inference and ML, App Store

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 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 Senior Data Scientist to own and drive data-driven strategy and deliver scalable ML and experimentation solutions for our product and business teams. As a key member of our diverse and multi-faceted organization you will 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. You will work collaboratively with partners across Business Marketing Product Content and Engineering daily to deliver material customer and business team is involved in all stages of the product development lifecycle from sizing ideation and prioritization to instrumentation and measurement AB testing and post-launch feature evaluation and incremental impact assessment. We also work on diverse collaborative projects around personalization app quality and review user segmentation subscriptions search etc. and touch on many parts of the App Store business.

Own and drive the data science strategy for product business and creative teams working on Apples our understanding of how users discover and engage with content and subscription services translating complex findings into actionable and scale experimentation frameworks to drive org-wide testing velocity including design measurement and interpretation of A/B tests and observational advanced ML causal inference techniques including synthetic control metalearning and counterfactual modeling to measure product impact in non-randomized and deploy ML models for customer scoring segmentation and lifetime value estimation to drive growth and acquisition LLMs and GenAI tools to develop innovative solutions to content and customer experience challenges augmenting data science workflows at the definition and prioritization of data infrastructure and tooling roadmap defining engineering and business intelligence requirements for new datasets and data technical direction and mentor data scientists across the organization enriching team output and fostering a culture of technical closely with business sponsors to lead and advise their roadmap and product strategy influencing cross-functional priorities at a senior level.

Bachelors degree in Computer Science Statistics Mathematics Engineering or related field.n7 years experience extracting insights from large datasets employing programming languages including Python and SQL.n7 years experience employing statistical methods to tackle business problems related to classification segmentation forecasting and customer lifetime experience architecting and scaling experimentation platforms including hypothesis testing metric tracking and experimentation expertise in causal inference methods including synthetic control diff-in-diff propensity score matching and regression discontinuity track record of building and deploying ML models that directly drive business decisions and product ability to set technical direction and influence cross-functional roadmaps at a senior interpersonal and communication skills with ability to translate complex technical concepts for non-technical stakeholders.

Masters or PhD in a quantitative productionizing ML models in collaboration with engineering with LLMs and GenAI applications in a production or customer-facing with distributed computing frameworks like with Marketing Mix Models and matched market testing.n