Data Scientist, Audio Telemetry Intelligence

Apple; Cupertino (CA); On-site; USD 145,000 - 264,000; Full time

Benefits offered by this job

Employee stock programs

Discretionary bonuses

Comprehensive medical and dental cover

Education reimbursement

Job summary

Apple, Inc. is seeking a Data Scientist for the Audio Telemetry Intelligence team in Cupertino, CA. You will analyze large-scale audio session and device telemetry to uncover patterns and drive predictive improvements in sound quality and user experience.

The role partners with data scientists and engineers to build reliable datasets, develop analytical workflows, and translate telemetry insights into product enhancements, with opportunities for growth and impact across Apple’s consumer devices.

Qualifications

• Bachelor's or Master’s in data science, ML, CS, or related field.
• 3+ years of full-time experience in data science, data engineering or ML.
• Strong Python for data analysis, scripting, and automation.
• Advanced SQL for querying and analyzing large-scale datasets.
• Experience building data pipelines and ETL/ELT workflows.
• Experience with big data processing frameworks (e.g., Apache Spark).
• Solid data modeling, data quality, and analytic dataset development.
• Proven ability to apply statistics or ML to behavioral data.

Responsibilities

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

Skills

Python

SQL

Data pipelines

ETL/ELT

Apache Spark

Data modeling

Statistical analysis

Machine learning

Education

Bachelor’s or Master’s degree in Data Science or related field

Job description

Data Scientist, Audio Telemetry Intelligence

Cupertino, California, United States Software and Services

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.

Minimum Qualifications

• Bachelor’s or Master’s degree in Data Science, Machine Learning, Data Engineering, Computer Science, or a related quantitative field.
• 3+ years of full-time 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.
• Proven work experience with applying statistical analysis or machine learning techniques to behavioral datasets.

Preferred Qualifications

• Experience working with telemetry, or time-series data.
• Familiarity with predictive modeling or pattern detection in large-scale data.
• Experience working with real-time or streaming data pipelines.
• Experience using AI-assisted development tools
• Proven 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.
• Experience using version control systems such as Git in collaborative environments.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $144,600 and $263,800, and your base pay will depend on your skills, qualifications, experience, and location.

• Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs.
• Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.
• You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition.
• Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
• Learn more about Apple Benefits.

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.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace. Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.