Principal Engineer- Powertrain Data Analytics

Responsibilities & Key Deliverables

• Key Tasks and Deliverables

  • Lead advanced machine learning initiatives to identify performance trends and anomalies in EV powertrains.
  • Design and implement interactive dashboards using Power BI for real-time analytics and stakeholder reporting.
  • Conduct sentiment analysis on product launches using Python-based web scraping techniques.
  • Enhance and customize Python packages to optimize data processing pipelines.
  • Develop predictive models utilizing regression analysis and artificial neural networks to assess vehicle behavior.
  • Apply Matlab or Python programming for algorithm development and simulation tasks.
  • Interpret EV vehicle telemetry and analyze customer usage patterns for strategic insights.
  • Architect solutions for data modeling, segmentation, and automation of customer datasets.
  • Lead prognostics analytics initiatives focused on powertrain lifecycle performance and fault prediction.

  2️. Critical Must-Have Deliverables

  • Deployment of at least two predictive models for EV powertrain performance or fault detection.
  • End-to-end dashboard creation in Power BI demonstrating vehicle performance metrics and customer insights.
  • Documented delivery of sentiment analysis reports using Python-based data acquisition.
  • Customization and optimization of Python libraries to support analytics scalability.

  3️. Good-to-Have Deliverables

  • Integration experience with vehicle digital twins or onboard analytics systems.
  • Insights from user experience data related to EV interface and charging behavior.
  • Cross-functional collaboration exposure with design or customer experience teams.
  • Authored whitepapers or patents in the EV predictive analytics domain.

Experience

• 16–18 years of proven experience in data analytics, with minimum 5 years in EV or automotive systems.
• Track record of delivering high-impact AI/ML projects focused on performance prediction or customer analytics.
• Hands-on experience with end-to-end data pipelines in automotive environments.

Industry Preferred

• Automotive OEMs and Tier-1 Suppliers
• EV Startups or Battery Analytics Companies
• Predictive Analytics or Mobility Platforms
• Smart transportation or digital vehicle solutions

Qualifications

• Bachelor’s in Mechanical, Automotive, or Electrical Engineering (B.Tech)
• Postgraduate specialization in Data Science, AI, or Automotive Systems is an advantage
• Certifications in Python, Power BI, or machine learning frameworks are highly preferred

General Requirements

Competencies and Skills

Functional Competencies

• EV powertrain architecture understanding
• Predictive modelling, machine learning (ANN, regression)
• Data visualization and storytelling

Tools and Techniques Used

• Expert-level Python programming and package modification
• Power BI, Matlab
• Web scraping and natural language processing for public sentiment
• Vehicle analytics platforms (e.g., CAN data interpretation)

Behavioral Competencies

• Analytical thinking and problem-solving orientation
• Cross-functional leadership and stakeholder engagement
• Innovative mindset with the ability to translate data insights into action