Nexotec - Automation | Machine Learning Engineer

Als Machine Learning Engineer bringe ich eine umfassende Erfahrung in der Entwicklung und Implementierung von Vorhersagemodellen und Datenpipelines mit, um messbare Geschäftsbeeinflussung zu erzielen.

• Big Data1 J.
• Cloud-Services
• Cloud Computing1 J.
• Data Analyst
• Machine Learning
• Predictive Analytics1 J.
• Pytorch
• Scikit-learn
• Tensorflow
• Well Engineer3 J.

Ergebnisorientierter Machine Learning Engineer mit über 3 Jahren Erfahrung im Liefern von umfassenden Lösungen für vorhersagende Wartung, Vorhersagen und Anomalieerkennung in großer Skala. Fachkenntnisse in Python, TensorFlow, PySpark und SQL, sowie in Cloud-Deploymen (Azure, AWS) und Datenpipelines, die messbare Geschäftsbeeinflussung erzielen.

Machine Learning Engineer and Data Scientist specializing in Predictive Maintenance, AI, and data-driven industrial solutions. I blend hands-on leadership in industrial operations with advanced data science, machine learning, and big data analytics, delivering measurable impact in operational efficiency, predictive insights, and innovation.

Proficient in Python, R, SQL, MATLAB, TensorFlow, PyTorch, Scikit-Learn, Pandas, PySpark, Docker, FastAPI, and Power BI, I specialize in data analysis, data cleaning, preprocessing, feature engineering, visualization, time-series forecasting, predictive modeling, anomaly detection, and data integration. I have experience building ETL pipelines, scalable data workflows, and production-ready data products from structured and unstructured datasets, leveraging cloud platforms (AWS, Azure, GCP) and DevOps practices (CI/CD, Git).

At Adani Total Gas Limited, I led a 6-member team managing 18 CNG stations, implementing ML-based operational forecasting, ETL automation, anomaly detection, and Power BI dashboards, resulting in reduced downtime and improved business performance. Currently, as a Master’s student and research assistant at RWTH Aachen University, I focus on Variational Autoencoders (VAE) for EV bearing fault detection, combining signal processing, data cleaning, feature extraction, anomaly detection, and ML modeling on large-scale sensor datasets.

I bring strong analytical, problem-solving, and cross-functional collaboration skills, working effectively with stakeholders, engineers, and researchers to deliver actionable insights. I am passionate about data-driven decision-making, statistical modeling, advanced visualization, and AI techniques to solve real-world challenges and drive business value.

I am eager to contribute to innovative projects in machine learning, predictive maintenance, and data science, collaborating across engineering and AI domains, and sharing expertise in data pipelines, big data, ETL, cloud computing, and advanced analytics.