Job Details

Role Number: 200643116-0836

Summary

Do you have a passion for invention and self-challenge? Do you thrive on pushing the
limits of what’s considered feasible? As part of our Battery Engineering group, you’ll
help craft creative battery solutions that deliver more energy in smaller spaces than
ever before! We work across subject areas to transform improved hardware elements
into a single, integrated design. Join us, and you’ll help us innovate new battery
technologies that continually outperform the previous iterations. By collaborating with
other product development groups across Apple, we push the industry boundaries of
what batteries can do and improve the product experience for our customers across the
world! This position works within a multi-functional team supporting the entire Battery
Department to identify trends, mine data, and help the battery team improve
performance.

Description

The Battery Analytics team transforms data into actionable insights by combining deep battery domain expertise with statistical, quantitative, and AI/ML methodologies.

Minimum Qualifications

• BS degree in Mechanical Engineering, Material Engineering, Electrical Engineering, Computer Science or relevant

• Experience with statistical analysis, data mining, or relevant

Preferred Qualifications

• Master’s degree, PhD or equivalent job-related experience in Mechanical Engineering, Material Engineering, Electrical Engineering, Computer Science or relevant

• Proven experience in statistical analysis, data mining, and causal inference methodologies

• Advanced proficiency in big data processing, visualization, and automated workflow development using Python, R, or similar scripting languages

• Hands-on experience with machine learning algorithms including ensemble methods, probabilistic networks, association rules, clustering, regression, neural networks, and large language mode

• Strong analytical problem-solving abilities to address urgent ad-hoc requests by integrating engineering knowledge with advanced analytics and ML techniques across diverse data sources

• Demonstrated expertise in anomaly detection techniques for time series and multivariate dataset

• Self-motivated contributor who proactively collaborates across functions and develops innovative solutions beyond existing toolsets

• Excellent communication skills with ability to explain complex technical concepts (particularly causal inference) to diverse audiences including data scientists, design engineers, and business stakeholders

• Battery technology experience strongly preferred

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .