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Metro location, mid-level generalist data role with common skills and 1–3 years experience.
Strong automotive telemetry and vehicle testing emphasis reduces cross-industry transferability despite generic data skills.
Explicit 1–3 years plus automotive domain knowledge and engineering analytics expectations create moderate strictness.
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Analyze vehicle fleet and test data to identify trends, performance characteristics, and anomalies.
Perform signal analysis and data interpretation to evaluate vehicle and component behaviour.
Develop data-driven insights and recommendations to support vehicle engineering and testing activities.
Bachelor’s degree in Computer Science, Mechanical, Automobile Engineering or related field.
1 to 3 years of work experience in automotive data analytics.
Proficiency in data analysis, vehicle data interpretation, statistical analysis, and engineering analytics.
Familiarity with MATLAB, Python, and R; knowledge of vehicle testing fundamentals.
Experience specifically in automotive data analytics and vehicle testing environments.
Strong analytical and problem-solving skills with ability to interpret complex datasets for engineering decisions.
Ability to collaborate effectively with cross-functional and global stakeholders to communicate findings.