Machine Learning & Data Scientist, OS Power & Performance

Position Overview

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 and 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 and communication of insights from large datasets. To be successful, you must have a strong foundation in statistical analysis and a robust software engineering background with the ability to write production level code. As a team member, you'll provide meaningful insights to various teams and influence decisions across Apple on a broad range of products.

Key Responsibilities

• Analyze high dimensional data to derive meaningful insights.
• Produce metrics, models, simulations, and tools for analysis and communication of insights from large datasets.
• Apply statistical analysis to solve business and product-development problems.
• Write production level code.
• Provide meaningful insights to teams and influence decisions across Apple on a broad range of products.

Required Qualifications

• Strong Quantitative Foundation: Education in Computer Science, Electrical Engineering, or a related quantitative field. Solid mathematical foundations, software engineering skills, and a broad knowledge of data analysis and practical machine learning are expected.
• Data Engineering and Analytics: Proven ability to transform raw data into actionable insights through practical problem formulation, building ETL processes (e.g. Python & Spark), and creating data visualizations (e.g. Tableau).
• Business Acumen and Problem-Solving: Ability to understand the broader business context, solve complex problems, and communicate findings effectively to stakeholders.
• Adaptability and Collaboration: Comfortable with ambiguity, eager to learn, and effective at working in collaborative environments with diverse stakeholders.

Preferred Qualifications

• M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a similar quantitative field, with strong statistical skills and intuition.
• Proficiency in distributed compute and 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.