About the job
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, we encourage you to apply!
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.
Qualifications
Minimum
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
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.