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Senior Data Scientist, Commerce Analytics for Apple Media Products


Job Description 

You will play a key role improving the AMP commerce & payments 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:
  1. Deep dives in large-scale data to identify key insights that inform product improvements and business strategy.
  2. Supervised and unsupervised learning, A/B testing and causal modeling.
  3. Define how best to measure and supervise commerce products and features.
  4. Engage with business, engineering, product management teams as a partner.
  5. Partner with other Apple organizations on data gathering, data governance, democratizing data with reporting tools and evangelizing critical metrics. 

Qualification 

  • 10+ years of professional experience in a data science or product analytics, preferably in payments or commerce
  • Strong passion for empirical analytics, data mining, and predictive analytics to develop impactful insights.
  • Experience in measuring UX impact, customer engagement, planning and analyzing A/B experiments.
  • Ability to partner with the data engineering and BI teams to provide requirements and to create project roadmaps for consistent data availability, quality, and accessibility.
  • Excellent collaboration and communication skills for communicating sophisticated quantitative analyses in a clear and detailed manner to senior business executives.
  • Be a self-starter, driven, accountable, and a high-energy teammate.
  • Train, mentor and provide critical feedback to junior data scientists to attain team-mandate.

Education 

Minimum of bachelor’s degree, preferably in computer science, statistics, economics, mathematics, engineering, economics, or related quantitative field.

Technical Skills 

  • Strong hands-on experience in ensuring data operations for large-scale data science and machine learning work.
  • Expert-level SQL skills with the ability to mine both structured/unstructured data. Ability to conceive and execute end-to-end scripted analytics solutions using SQL/TeraData and at least one large-scale data languages such as Scala or PySpark
  • Proven proficiency in data architecture covering scalable schema design, relational and non-relational database technologies, data warehousing principles, modern ETL, aggregation/ projection strategy, code management, and performance optimization.
  • Experience in data visualization tools such as Tableau for dashboard building.
  • Expertise in statistical data analysis for unsupervised & supervised learning algorithms, multivariate techniques and applied regression techniques.
  • Prior experience in working on payment products or large multinational marketplaces/e-commerce businesses.
  • Excellent communication and presentation skills with meticulous attention to detail and ability to communicate optimally between business and analytic teams.

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