App Store Senior Marketing Data Scientist

App Store Senior Marketing Data Scientist

Culver City, California, United States Software and Services

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.

Partner with Business and Engineering to define data collection, reporting requirements, metrics, and aggregates for analysis, ETLs, reporting, experimentation and machine learning. Investigate large-scale data to uncover trends and identify key insights that will propel marketing strategies. Determine marketing's incremental effect on our App Store business, primarily through paid channels. Build datasets and automated dashboards to monitor channel and campaign performance.

Help design marketing campaign touchpoints along the customer journey and optimize engagement. Develop effective attribution logic that serves as benchmarks for optimization. Provide ad-hoc analysis and support for tentpole campaigns. Establish propensity models to refine campaign audience selection. Explore applying cutting‑edge generative AI technologies to drive increased business value. Collaborate with Business, Marketing, Finance, and Executive teams to generate regular presentations for C-level executives.

Partner with other Apple organizations on data gathering, data governance, evangelizing key performance indicators and democratizing data.

• 4+ years of demonstrated ability in a Data Scientist or Data Analyst role, preferably for a digital media, Mar Tech, digital subscription business, or technology business.
• Strong proficiency with SQL, Python or R.
• 4+ years applied experience in building sophisticated datasets that enable data science and BI. Experience working with structured and unstructured data stored in distributed file systems.
• Solid experience working in marketing campaign measurement for both paid and non‑paid campaigns.
• Experience with standard marketing data science analysis to include experimental design, linear regression, clustering, survival, and quasi‑causal analysis.
• Curious business mindset with an ability to condense complex concepts and analysis into clear and concise takeaways that drive action.
• Bachelor's degree in Computer Science, Economics, Engineering, Mathematics, Data Science, Statistics or equivalent professional experience.

• Experience in a digital subscription business or large‑scale e‑commerce platform.
• Skilled at measuring advertising value through causal inference techniques.
• Advanced degree in a related field preferred.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $137,500 and $250,700, and your base pay will depend on your skills, qualifications, experience, and location.

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