Job Description
Summary
You will play a key role understanding and optimizing the businesses under Apple Services as a part of the Revenue and Subscriptions Data Science team. As a member of this team, you will help us to grow the financial, transaction, and subscription health of our businesses by sizing, measuring, and recommending impactful initiatives. Responsibilities will include understanding the impact across in-app purchases, subscription renewals, payment authorizations, transaction efficiencies across multiple lines of businesses.
Description
As a part of this team, you will employ sophisticated analytic tools such as A/B testing and causal modeling to accurately understand the effect of multiple and often interrelated initiatives; build and maintain positive relationships with key partners across the company to successfully deliver actionable insights; and collaborate with business, marketing, finance and executive teams to generate regular presentations for C-level executives.
Minimum Qualifications
- 5+ years of professional experience in data science, machine learning, or digital product analytics
- Mastery in SQL-based languages, and proficiency large-scale data languages such as PySpark
- Proven record measuring user experience behavior, customer engagement, and business impact using sophisticated and appropriate analytic tools
- Strong proponent of experimental test and design, and practical experience with interpreting observational results
- Excellent communication and presentation skills with meticulous attention to detail with the ability to communicate effectively between business and analytics teams
- Strong verbal and written communication and presentation skills across both technical and non-technical audiences
- Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field
Preferred Qualifications
- Experience in a digital subscription business or for an e-commerce platform
- Masters\' degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Economics or related field