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Data Scientist, Commerce Analytics - NYC at Apple (New York, NY)

At Apple, extraordinary ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. If you are a self-motivated and passionate individual who is not afraid of challenges, were looking for you to join the Wallet, Payments & Commerce (WPC) Analytics organization. The WPC Analytics team supports all commerce, payments & subscription platforms across all of Apples Services business (App Store, iTunes, Music, Books, TV+, iCloud, Apple Wallet). You will be a thought partner to the business, understand their goals and then use your skills and subject matter expertise to surface impactful insights that drive business and customer benefits. You will collaborate with partners across product, design, engineering, and business teams to drive your findings and recommendations into action. Our culture is about getting things done iteratively and rapidly, with open feedback and debate along the way; we believe analytics is a team sport, but we strive for independent decision-making and taking smart risks.

You will play a key role improving the AMP commerce, payments & subscription platform. As a member of this team you will help optimize the platform by developing new data products and tuning existing features. A few areas your work will influence include account and payment creation flows, transaction efficiency and authorizations, and subscription management and renewals. Your day to day activities will include:

Deep dives in large-scale data to identify key insights that inform product improvements and business strategy.

Supervised and unsupervised learning.

A/B testing and causal modeling.

Define how best to measure and supervise commerce products and features.

Engage with business, engineering, product management teams as a thought partner.

Build and maintain positive relationships with key partners across the company to optimally deliver measurable insights.

Partner with other Apple organizations on data gathering, data governance, democratizing data with reporting tools and evangelizing critical metrics.

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