Apple’s App Store is the world’s largest and most innovative app marketplace, home to over 1.5 million apps and serving more than half a billion customers every week across all the Apple devices. Since the App Store launched in 2008, it has changed how we all live; it has enabled countless new companies, spawned new industries, and built millions of jobs. But we believe we are just getting started.

Do you have a strong passion for using data to drive business decisions, generate ideas, and inspire collaborators? As a Data Analytics Engineer on the App Store Data team, you will play an integral role in helping App Store make decisions using data and improve the store every day for both users and developers by generating analysis from data in a privacy-friendly manner. We enable data-driven innovation by building solutions, services, and analytics for a variety of internal stakeholders and external partners. In a world where apps have become essential in people’s daily lives, the App Store team has become essential to Apple’s business.

As a member of the App Store Data team, you will have significant responsibility and influence in shaping its strategic direction. The data we produce power Apple leadership and partners about new innovations and the next big things. To succeed here you’ll need to be a proponent of building world-class analytical solutions. To join us in our next industry-leading software project you will be expected to be part of our very impactful multi-functional team.

Your role will be to analyze data, spot trends and patterns, and use your findings to give actionable recommendations that help our business grow

You’ll need to communicate your insights clearly to different teams and stakeholders
Collect, process, and analyze large datasets using SQL, Python or Scala in big data ecosystem

Contribute to large-scale quantitative analysis projects through all phases; this includes data quality, data modeling, algorithm/feature development, statistical analysis, and data visualization

Apply research and analytical skills to monitor and analyze suspicious user/device patterns, anomalies and consolidate anti-fraud rules to mitigate usage based billing fraud.

B.S. in a quantitative field (e.g., Statistics, Economics, Computer Science, Mathematics, Engineering).At least 5+ years of experience as a Data Analytics Engineer with excellent analytical and problem-solving skills.Advanced programming skills in data manipulation & processing (SQL, Python and Scala).Experience in the big data ecosystem (e.g. Hadoop, Spark, Iceberg, Trino, Airflow).Proven expertise in data wrangling and developing data visualizations & reporting with toolings such as Tableau, Superset etc.Strong understanding of data analytics, structured and unstructured data analysis, predictive modeling techniques to implement Fraud detection, identify patterns in data and data visualization as well as a good command of emerging methodologies like artificial intelligence.Outstanding verbal and written communication skills, along with strong collaborative abilities.