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:
- 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 partner.
- 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.
