I am a Mechanical Engineer with extensive experience in automotive systems validation, data analysis, and engineering problem solving. My professional background includes working as a Systems Development and Application Engineer at Bosch, where I specialized in fuel injection equipment and exhaust aftertreatment systems. I have hands-on experience in instrumentation, testing, calibration, and analysis of engineering data.
Throughout my career, I have contributed to Industry 4.0 initiatives by developing SQL queries, Python scripts, and Power BI dashboards to optimize industrial data pipelines and improve process efficiency. This blend of engineering fundamentals and data science has enabled me to approach problems analytically and deliver actionable insights.
I hold a Master’s degree in Mechanical Engineering and an MBA in Data Science, which complement my technical expertise with advanced analytical skills. I am passionate about applying engineering principles to AI model training and validation, combining my knowledge of mechanical systems with programming and data analysis.
My experience at Bosch involved rigorous testing and validation of automotive systems, including diesel calibration and emissions performance analysis. I am proficient in using tools like ETAS INCA and MDA for CAN data analysis and have supported both bench and vehicle testing environments.
I am eager to contribute to AI projects by leveraging my engineering background and Python-based validation skills. I believe that integrating sound engineering reasoning into AI model evaluation can significantly enhance the accuracy and reliability of AI systems.
I am open to remote work opportunities where I can apply my expertise to support AI training and development, ensuring that engineering logic and real-world technical considerations are reflected in AI solutions.
Thank you for considering my application. I look forward to the possibility of contributing to innovative projects that bridge engineering and artificial intelligence.
Instrumentation, testing and validation of exhaust aftertreatment systems (EGT/DNOX) and fuel injection equipment. Diesel calibration and analysis of vehicle emissions performance. Acquisition and interpretation of measurement data using ETAS INCA and MDA. Execution of bench and vehicle tests supporting engineering validation activities.
Supported instrumentation and validation of aftertreatment systems and fuel injection equipment. Collected and processed CAN-based testing data for engineering analysis. Assisted validation activities for passenger and off highway vehicle applications.
Implemented industrial data collection systems connecting machines to databases. Developed SQL queries and Power BI dashboards to monitor production KPIs. Applied data analytics methods to identify process anomalies and efficiency improvements.
Master’s Degree in Mechanical Engineering
MBA in Data Science
Bachelor’s Degree in Mechanical Engineering
Bachelor’s Degree in Production Engineering
International Mechanical Engineering Studies
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