Data Scientist - Battery at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Jun, 26

Salary

0.0

Posted On

04 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Statistical Analysis, Data Mining, Causal Inference, Big Data Processing, Visualization, Automated Workflow Development, Python, R, Machine Learning Algorithms, Ensemble Methods, Probabilistic Networks, Association Rules, Clustering, Regression, Neural Networks, Large Language Models

Industry

Computers and Electronics Manufacturing

Description

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

Responsibilities

This role involves transforming data into actionable insights by combining deep battery domain expertise with statistical, quantitative, and AI/ML methodologies. The individual will support the entire Battery Department by identifying trends, mining data, and helping to improve battery performance.