Description

You will collect, visualize, and analyze data to improve the correlation between digital twin models and physical testing.

Responsibilities

• Translate complex data into engineering presentations to communicate findings and model correlation results.
• Collaborate with engineering, testing, and project teams to develop test plans and interpret data for design recommendations.
• Synthesize simulation results, technical requirements, and historical data to identify functional improvements for heavy-duty trucks.
• Work with cross-functional teams to interpret durability, crash, and NVH data to drive digital twin model accuracy.
• Coordinate with global technical strategy teams to improve simulation strategies through data analysis.

Required Skills

• 5+ years of experience in data analysis, specifically within the automotive or transportation industry.
• Proficiency in Python and SQL for statistical analysis and data manipulation.
• Experience with Database Management Systems (BDMS) and querying data.
• Advanced data visualization skills using PowerBI.
• Strong background in durability and fatigue analysis fundamentals.
• Knowledge of machine learning techniques for data analysis and predictive modeling.
• Experience working within Agile methodologies.
• Ability to apply statistical methods to extract insights and drive data-driven decisions.
• Bachelor's Degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Master's Degree in a related field.
• Experience specifically with heavy-duty vehicles.

Key Skills

Education

Bachelor's Degree in Computer Science