Data Scientist – Battery Analytics

• Company Apple
• No. of Openings 10+
• Salary Not Disclosed
• Work Type on-site

Job Description :

Key Qualifications

Battery Engineering expertise, analytics, statistical, and ML skills

Knowledge of data mining and ML algorithms including ensemble-based approach, probability networks, association rules, clustering, regression, and neural networks

Strong problem-solving skills to address ad-hoc analytics request with by using engineering knowledge and analytics/ML skills based on different data source.

Expertise to using big data and ML to predict battery performance based on early cycle data at qualification stage

Strong expertise to process and visualize big data as well as automate process using a scripting language (Python, R, etc.)

Self-starter to interact with other functions in matrix environment, proven creativity to go beyond current tools to deliver the best solution to the problem;

Effective interpersonal skills to articulate difficult technical topics, especially causal inference, to collaborators including peer data scientist, design engineers, and business partners.

Description

The goal of the Battery Analytics team is to turn data into practical insights using battery knowledge as well as statistical, quantitative, and machine learning technologies.


•Analyze factory, field, and failure data and use engineering understanding to collaborate with multi-functional teams to resolve battery issues. Quick study to understand end to end nature of Apple DB to organize accurate sample size, proper data pull and minimize SQA issues with maximum efficiency.

•Design, implement, process and workflow and interpret data; Apply advanced technologies, for modeling improvements, especially to drive causation with world class battery mechanistic expertise.

•Develop time-series data and cycling data visualization and analytics capability, conduct comparative study, identify early signals, lead investigation for FA.

•Lead resolution of out of family forecasts for KPI’s such as swell, impedance, and capacity

•Solid understanding of Python, JMP, SQL, and Tableau

Education & Experience

An academic background is in engineering, science, or quantitative field such as ME, EE, Materials, Statistics, Computer Science, Mathematics, Physics, or similar. Prefer advanced degree or bachelor with 3-5 years of relevant experience.