Data Scientist II, Battery & Charging - Powertrain Data

We are seeking a passionate and analytical Data Scientist to support our Powertrain Battery and Charging teams. This role will focus on charging system fault and failure prediction, and battery model development. You will play a key role in providing the visualization results for data-driven decision-making across design, R&D, manufacturing, and field operations by transforming complex data into actionable insights.

The ideal candidate will combine a solid foundation in data science with an understanding of engineering systems to deliver impactful analytics, enhance operational performance, and support product improvement initiatives. This includes developing robust dashboards, performing advanced analyses, and working closely with cross-functional teams to ensure data integrity and alignment with business objectives.

Key Responsibilities:

• Collaborate with engineering teams to define and track key performance indicators (KPIs) for charging performance, battery management systems, and battery pack manufacturing processes.
• Design and develop interactive dashboards and automated reports to visualize system performance, degradation trends, and operational insights.
• Conduct exploratory data analysis and apply statistical modeling to support root cause investigations and reliability engineering efforts.
• Lead efforts to enhance data quality, standardization, and infrastructure scalability across teams and systems.
• Effectively communicate technical findings to diverse audiences, including executives, engineers, and manufacturing stakeholders.

Required Qualifications:

• Bachelor’s degree with 4+ years of experience, or Master’s degree with 2+ years, in Data Science, Engineering, Statistics, or a related field.
• Proficient in Python, SQL, and PySpark for data analysis, automation, and visualization.
• Practical experience with dashboarding tools such as Tableau and Apache Superset.
• Background in machine learning algorithms using frameworks like TensorFlow or PyTorch.
• Excellent problem-solving skills, with strong attention to detail and the ability to excel in fast-paced, engineering-driven environments.
• Effective communicator with proven ability to collaborate across both technical and non-technical teams.

Preferred Qualifications:

• Background in Mechanical or Electrical Engineering with a solid understanding of charging systems and battery fundamentals.
• Experience in developing models using deep learning algorithms.
• Industry experience in the automotive or electric vehicle (EV) domain, with a focus on EV charging systems, battery pack manufacturing processes, or battery management system analytics.