About

Mohamed Zaid Jendoubi is a versatile software engineer with a strong programming background and a passion for data analytics and machine learning. He is currently working as a Machine Learning Engineer at Think-it, where he is responsible for developing and deploying reliable solutions for partners such as BMW, Pro-drone, and Genetic Intelligence. He is also leading the Think-it internal data science team in developing a chatbot to improve the recruitment process by answering potential candidates' questions. Mohamed has a wealth of experience in the field of machine learning, having previously worked as a Machine Learning Engineer at Pro-Drone, where he implemented a solution to detect and classify different kinds of damages located on the wind turbine blades surface. He also trained a Faster R-CNN model to detect damages in the wind turbine blades and validated and visualized the prediction results. At BMW, Mohamed implemented a PoC to analyze driver behavior, explored and analyzed vehicle telemetry streaming data, and trained and deployed a neural network to predict the driver class using Amazon SageMaker. Mohamed has a degree in Software Engineering from the National Institute of Applied Science and Technology, where he honed his skills in ML, data science, CNN, AWS, Scikit, object detection, Python, Pandas, Sagemaker, computer vision, AI, object detection, Tensorflow, software engineering, Amazon Kinesis, neural networks, research scientist, mobile, and Keras. He is proficient in various data analytics techniques and is passionate about turning data into insights to build better solutions. Mohamed is an expert in AWS, Google Cloud, NLP, Computer Vision, Tensorflow, and Python. He has also held internal and external machine learning workshops and is committed to sharing his knowledge and expertise with others. With over 6 years of relevant experience, Mohamed is a data science and machine learning engineer who is dedicated to using his skills to develop innovative solutions and drive business growth.