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 & 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 value.
Our 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 Apple's Services.
Lead our understanding of how users discover and engage with content and subscription services, translating complex findings into actionable recommendations.
Architect and scale experimentation frameworks to drive org-wide testing velocity, including design, measurement, and interpretation of A/B tests and observational studies.
Apply advanced ML causal inference techniques including synthetic control, metalearning, and counterfactual modeling to measure product impact in non-randomized settings.
Develop and deploy ML models for customer scoring, segmentation, and lifetime value estimation to drive growth and acquisition strategy.
Leverage LLMs and GenAI tools to develop innovative solutions to content and customer experience challenges, augmenting data science workflows at scale.
Lead the definition and prioritization of data infrastructure and tooling roadmap, defining engineering and business intelligence requirements for new datasets and data products.
Set technical direction and mentor data scientists across the organization, enriching team output and fostering a culture of technical rigor.
Work closely with business sponsors to lead and advise their roadmap and product strategy, influencing cross-functional priorities at a senior level.
Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related field.
7+ years experience extracting insights from large datasets, employing programming languages including Python and SQL.
7+ years experience employing statistical methods to tackle business problems related to classification, segmentation, forecasting, and customer lifetime value.
Demonstrated experience architecting and scaling experimentation platforms, including hypothesis testing, metric tracking, and experimentation strategy.
Strong expertise in causal inference methods including synthetic control, diff-in-diff, propensity score matching, and regression discontinuity design.
Proven track record of building and deploying ML models that directly drive business decisions and product outcomes.
Demonstrated ability to set technical direction and influence cross-functional roadmaps at a senior level.
Strong interpersonal and communication skills with ability to translate complex technical concepts for non-technical stakeholders.
Master's or PhD in a quantitative field.
Experience productionizing ML models in collaboration with engineering teams.
Experience with LLMs and GenAI applications in a production or customer-facing context.
Experience with distributed computing frameworks like Spark.
Experience with Marketing Mix Models and matched market testing.
We’re a diverse collection of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways. The people who work here have reinvented entire industries with the Mac, iPhone, iPad, and Apple Watch, as well as with services, including iTunes, the App Store, Apple Music, and Apple Pay. And the same passion for innovation that goes into our products also applies to our practices — strengthening our commitment to leave the world better than we found it.
There’s a place here for every kind of brilliant. Everyone here is an innovator, or an innovator-to-be, no matter what your team or your role. So bring your passion, courage, and original thinking and get ready to share it, because every new product, service, or feature we invent is the result of people working together to make each others’ ideas stronger. Innovation at this level depends on people who represent the variety of the human experience and inspire us with their own fresh perspectives. Together, we’ll do amazing work that can make a difference in people’s lives. Including your own. Learn more about working at Apple.