Description

You will apply data science and control systems theory to solve complex engineering challenges in Powertrain Engineering.

Responsibilities

• Apply control systems and closed-loop feedback principles to numerical and data-driven system simulations.
• Develop and deploy models using regression, clustering, neural networks, and time series analysis for prediction and real-time optimization.
• Execute predictive analysis to drive automated decision-making processes.
• Design IoT-based instrumentation and data logging workflows to build and validate engineering models.
• Create impactful data visualizations to transform raw data into actionable knowledge.

Required Skills

• 5+ years of experience in data modeling and predictive analysis.
• Proficiency in Python (Numpy, SciPy, Pandas, Tensorflow), R, and SQL.
• Hands-on experience with Matlab/Simulink and control systems.
• Working knowledge of Git, Azure, Hadoop, and pySpark.
• Experience with C, C++, or Scala.
• Strong understanding of relational databases and data privacy.
• Expertise in data visualization tools such as Power BI, QlikView, or Tableau.
• Background in Mechanical, Automobile, Electronics, Mechatronics Engineering, or Data Science.

Preferred Skills

• Experience with plant/component models and integration into SIL/MIL/HIL evaluations.

Key Skills

Education

Any Graduate