Data Scientist - Wallets, Payments and Commerce

Full time

Employment Information

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Apple is a place where extraordinary people gather to do their best work. Together we craft products and experiences people once couldn’t have envisioned — and now can’t imagine living without. If you’re excited by the idea of making a real impact and joining a team where we pride ourselves in being one of the most diverse and expansive companies in the world, a career with Apple might be your perfect job. The Wallets, Payments, and Commerce (WPC) team at Apple is looking for a full-stack Data Scientist who is passionate about crafting and implementing data solutions that have a direct and measurable impact on Apple customers. You will employ predictive modeling and statistical analysis to build end-to-end solutions for improving the adoption of Apple wallet, alternative payment methods, and core commerce platform. You will be a thought partner to the business, understand strategic goals, and then use your skills and subject matter expertise to surface impactful insights that drive business decisions and customer benefits. You will collaborate with partners across product, design, engineering, and business teams to drive your recommendations into action. Our culture is about getting things done iteratively and rapidly, with open feedback and debate along the way. We believe Data Science is a team sport, but we strive for independent decision-making and taking smart risks.

Key Qualifications

  • Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop
  • Ability to implement data science pipelines and applications in a general programming language such as Python, Scala, or Java
  • Practical experience with and theoretical understanding of ML algorithms for classification, regression, clustering, and anomaly detection
  • Ability to extract significant business insights from data and identify the roots behind the patterns
  • Communication skills for communicating complex quantitative analyses to senior business executives


  • Take deep dives in large-scale data to identify key insights that will shape future product strategy
  • Collaborate with cross-functional teams to identify new growth opportunities, develop data requirements, establish product critical metrics, and evangelize data products
  • Design, deploy, and evaluate experiments that help define opportunities for higher adoption, improved business performance, and better customer experience
  • Conduct hypothesis-driven exploratory analyses, select appropriate ML algorithms, and build complex optimization engines to deliver impactful data solutions
  • Research new technologies and methods across data science and data engineering to improve the technical capabilities of the team
  • Communicate insights to senior management by distilling complex analysis and concepts into concise business-focused takeaways

Education & Experience

Minimum of bachelor’s degree, preferably in engineering, 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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