Data Scientist - Battery
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.","responsibilities":"Analyze multi-source data (factory, laboratory, field, and failure data) and collaborate with cross-functional teams to resolve battery performance issues
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Navigate Apple's database ecosystem to efficiently extract representative datasets while maintaining data quality standards for data-driven analysis
Design and implement robust data processing workflows; apply advanced modeling techniques with emphasis on causal analysis leveraging battery physics knowledge
Build comprehensive time-series and battery cycling data visualization and analytics capabilities
Conduct comparative studies, identify early warning signals, and lead failure analysis deep-dives
Drive resolution of anomalous forecasts for critical KPIs including battery swell, impedance, and capacity fade
Develop AI/ML capability for battery engineering leveraging state-of-the-art GenAI progress
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
Minimum Qualifications
BS degree in Mechanical Engineering, Material Engineering, Electrical Engineering, Computer Science or relevant
Experience with statistical analysis, data mining, or relevant
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 .
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion
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