Machine Learning & Data Scientist, OS Power & Performance

Apple; Cupertino (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Apple in Cupertino seeks a Senior Machine Learning & Data Scientist to analyze high-dimensional data and develop data products that influence hundreds of millions of users. You will derive insights, build models, simulations, and tools, and communicate findings effectively to teams.

You will apply rigorous statistical analysis and production-level coding skills to solve business and product challenges, collaborating across software and hardware teams.

Qualifications

• Bachelor's degree in a quantitative field (CS/EE/Math) or equivalent.
• Strong foundation in statistics, data analysis, and software engineering.
• Experience transforming raw data into actionable insights; familiarity with ETL (Python/Spark) and visualizations.

Responsibilities

• Analyze high-dimensional data to derive actionable insights.
• Produce metrics, models, simulations, and tools for analysis and communication.
• Apply statistics to business and product-development problems.
• Write production-level code.
• Influence decisions across Apple with cross-functional insights.

Skills

Quantitative reasoning

Software engineering

Statistical analysis

Cross-functional collaboration

Education

B.S. in CS/EE/Math

MS/PhD preferred

Tools

Python

Spark

Tableau

Kubernetes

Airflow

Job description

Summary

Great performance is critical to Apple's product experience. We are seeking a Senior 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,

Description

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.

Key Responsibilities

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

Minimum Qualifications

• Strong Quantitative Foundation: Education in Computer Science, Electrical Engineering, or a related quantitative field.
• Strong mathematical foundations, software engineering, and broad knowledge of data analysis and practical machine learning are expected.
• Data Engineering and Analytics: Skilled at scalably transforming raw data into actionable insights through practical problem formulation followed by building of ETL processes (e.g. Python & Spark) and 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 capable of working effectively in a collaborative environment. Strong interpersonal skills and the ability to build relationships with diverse stakeholders are essential.

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 & 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.