Data Scientist Audio Analytics

Imagine what you could do at Apple! Everyday, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Do you bring passion and dedication to your job? If so, we are looking for individuals like you. The Media Graphics Compute Technologies (MGC) group is at the center of audio, video, and graphics in Apple's innovative products, including the iPhone, iPad, Mac, Apple Watch, AirPods, HomePod, Apple TV and Vision Pro. Our work directly impacts the end-user experience through impactful features such as Adaptive Noise Control, Conversation Awareness, FaceTime, Siri, media playback, and Conversation Boost, to name just a few.

We're seeking an experienced Data Scientist to join our Audio Technology team, focusing on developing and optimizing audio experiences across our portfolio of consumer electronics. You'll work at the intersection of audio engineering, machine learning, and user experience, analyzing complex datasets to drive improvements in sound quality, noise cancellation, voice recognition, and acoustic performance.

Description

We are seeking a Data Scientist to help advance telemetry intelligence for device experience optimization. This role focuses on analyzing large-scale audio session and device telemetry data to uncover patterns in user behavior and system adjustments, enabling opportunities for predictive and adaptive system improvements.

The ideal candidate combines strong data analysis and programming skills with experience working with large-scale datasets. This role will partner with data scientists and engineers to build reliable datasets, develop analytical workflows, and translate telemetry insights into data-driven improvements to device audio experiences.

","responsibilities":"

Analyze large-scale audio session and device telemetry data to identify patterns in user behavior and system adjustments.

Develop analytical datasets and workflows that support scalable analysis and experimentation.

Build and maintain data pipelines that transform raw telemetry into reliable analytical datasets.

Explore opportunities for predictive or adaptive system behaviors that improve device audio experience.

Partner with engineering and product teams to translate telemetry insights into actionable product improvements.

Improve data accessibility and reliability through automation and internal data tooling.

Support experimentation and data-driven decision making across audio and device interaction scenarios.

Preferred Qualifications

Experience working with telemetry, or time-series data.

Experience applying statistical analysis or machine learning techniques to behavioral datasets.

Familiarity with predictive modeling or pattern detection in large-scale data.

Experience working with real-time or streaming data pipelines.

Familiarity with data visualization tools such as Tableau, matplotlib, or seaborn.

Experience working with large-scale data platforms or cloud-based data infrastructure.

Strong communication skills with the ability to translate complex data insights into actionable recommendations.

Minimum Qualifications

Bachelor's or Master's degree in Computer Science, Electrical Engineering, Data Science, or a related quantitative field.

3+ years of professional experience in data science, data engineering, or machine learning related roles.

Strong programming skills in Python for data analysis, scripting, and automation.

Advanced SQL skills for querying and analyzing large-scale datasets.

Experience building or maintaining data pipelines and ETL/ELT workflows.

Experience working with large-scale or distributed data processing frameworks (e.g., Apache Spark).

Solid understanding of data modeling, data quality, and analytical dataset development.

Experience using version control systems such as Git in collaborative environments.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .