Apple-posted 4 months ago
San Diego, CA
5,001-10,000 employees

Great performance is critical to Apple's product experience. We are seeking a Machine Learning & Data Scientist to help with quantitative analysis of high dimensional data to draw insights that would impact hundreds of millions of users. If the idea of developing data products to improve Apple’s software & hardware performance excites you, we encourage you to apply! We're looking for a proactive & impact-driven engineer with excellent machine learning, analytical, problem solving and communication skills. In this role, you will analyze high dimensional data to derive meaningful insights and be responsible for producing metrics, models, simulations, and tools for analysis & communication of insights from large datasets. To be successful, you must have a strong foundation in statistical analysis and the ability to apply it to solving business & product-development problems, as well as a strong software engineering background with the ability to write production level code. As a member of this team, you will have the opportunity to provide meaningful insights to teams and influence decisions across Apple on a broad range of products.

  • Analyze high dimensional data to derive meaningful insights.
  • Produce metrics, models, simulations, and tools for analysis.
  • Communicate insights from large datasets effectively.
  • Transform raw data into actionable insights through practical problem formulation.
  • Build ETL processes and data visualizations.
  • Education in Computer Science, Electrical Engineering, or a related quantitative field.
  • Strong mathematical foundations and software engineering skills.
  • Broad knowledge of data analysis and practical machine learning.
  • Skilled at transforming raw data into actionable insights.
  • Ability to understand the broader business context and solve complex problems.
  • Strong interpersonal skills and ability to build relationships with diverse stakeholders.
  • M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a similar quantitative field.
  • Proficiency in distributed compute & storage technologies such as HDFS, S3, Iceberg, Spark, and Trino.
  • Proficiency with designing ETL flows and automation/scheduling (e.g. Kubernetes and Airflow).
  • Working knowledge of Operating Systems.
  • Experience driving cross-functional projects with diverse sets of stakeholders.
  • Skilled at connecting data insights to the company's overall strategy and objectives.
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