Data Scientist, Commerce Analytics – NYC

Job Overview

Key Qualifications

5+ years of professional experience in a data science or product analytics

Strong passion for empirical analytics, data mining, and predictive analytics to develop measurable 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 build project roadmaps for consistent data availability, quality, and accessibility.

Excellent collaboration and communication skills for presenting complex quantitative analyses in a clear and detailed manner to senior business executives.

Be a self-starter, driven, accountable, and a high-energy teammate.

Ability to conceive and execute end-to-end scripted analytics solutions using SQL/TeraData, Spark SQL, PySpark, Hadoop!

Knowledge of Big Data and relational database structures, data warehousing principles, and expert-level SQL skills with the ability to mine both structured/unstructured data

Deep expertise in data analysis with familiarity with multiple programming languages, platforms, tools, methodologies,

Experience in data visualization tools such as Tableau for full-stack data analysis, insight synthesis, and presentation.

Prior experience in working on payment products or large multinational marketplaces/e-commerce businesses.

Description

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.

Education & Experience

Minimum of bachelor’s degree, preferably in economics, statistics, computer science, or related quantitative field. Advanced degree in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.

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