Apple seeks to hire a senior leader of Marketing Science for the Wallet, Payments & Commerce Analytics group. Reporting to the head of Data Science for Apple Pay, this person will be responsible for leading marketing science and customer insights across ApplePay, App Store & iTunes Gift Card, as well as Payments and Commerce for the multi billion dollar services sector at Apple. We are seeking an experienced senior professional to manage a team of data scientists to design, develop, and field analyses and tools that have direct and measurable impact to the customer experience and business outcomes. We are looking for someone that is passionate about building analytics practices to solve complicated business problems and deliver on our strategies. Self-directed with wide range of technical skills, and are highly proficient in turning data discoveries into analytical insights and products that drive business and customer outcomes. This role is meaningful tactically and strategically and requires a mix of high level leadership and deep experience directing the activities of a highly applied and deliverables focused team. The team will also conduct analytics and forecasting for a broad range of strategic and tactical questions related to ApplePay including CRM activities related to customer acquisition, lifecycle, and retention across our services and subscriptions business at Apple.
You are a top-tier data scientist with demonstrated ability in forming teams, coordinating analytical processes and workflows, and mentoring junior team members
Have a passion for applied empirical analytics and answering hard questions with data, and the demonstrated ability to conceptualize, promote and implement business insights
Confirmed collaboration, communication and story telling skills with ability to adapt and connect across a variety of audiences. This includes strong writing, and data visualization skills with the ability to communicate complex quantitative analysis in a clear, detailed, and measurable manner to senior executives.
Partner with senior leaders across the three focus areas to understand business goals, consult on data strategies and produce repeatable outcomes
Handle econometric analytics projects through all phases, including data quality, data modeling, statistical analysis, data visualization and presentation of results.
Leading ongoing and ad-hoc analyses and predictive analytics to provide leadership with meaningful insights at tactical and strategic levels.
Partner with the data engineering and BI team to Run workflows, requirements and project roadmap with Apple's IT organization to ensure consistent data availability, data quality and data accessibility for your projects.
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