Senior Data Analyst - Storage Technologies, Core OS
Confirmed live in the last 24 hours
Apple
Job Description
Summary
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. As a Data Analyst on Apple’s Storage Analytics team, you’ll play a key role in developing the fastest, most efficient SSDs for products including iPhone, iPad, Apple Watch, and Apple Silicon Macs. We’re seeking an exceptional analyst with expertise in distributed data processing and a proven ability to transform data into actionable insights. If you’re passionate about advancing how data is used to make Apple’s products even better, we’d love to hear from you!
Description
On the Storage Data Analytics team, we are responsible for ad hoc data analysis, developing and maintaining distributed data pipelines, and creating and supporting analysis tools. Our work focuses on Apple’s storage solutions. The team is small and nimble, able to quickly explore ideas and present them to both storage teams and leadership.
Minimum Qualifications
4+ years of experience in data analytics Professional programming experience with Python Experience working with relational databases and SQL Ability to lead data investigations and analysis projects with ambiguous requirements Advanced knowledge of statistics and modeling Experience visualizing and presenting analyses using tools such as Jupyter and Tableau Excellent written, verbal, and data communication skills BS in Computer Engineering, Computer Science, Physics, Mathematics, or equivalent experience/skills
Preferred Qualifications
Master’s or PhD in Computer Engineering, Computer Science, Physics, Mathematics, or equivalent experience/skills Familiarity with distributed computation, storage, and workflow management (e.g., Splunk, Spark, Kubernetes, Kafka, Hadoop, MapReduce, Airflow, etc.) Knowledge of storage concepts, SSDs, and I/O paradigms Highly organized, creative, motivated, and results-driven
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