Muhammed Guelsen

Machine Learning Engineer

Professional Overview
Muhammed Guelsen is an accomplished Machine Learning Engineer with a strong background in research and development. He possesses a versatile skill set spanning technical expertise, problem-solving, and industry-specific knowledge, which he leverages to drive innovation and deliver impactful solutions.

Experience Summary

Current Role
As a Machine Learning Engineer at fraud.com, Muhammed is responsible for developing and optimizing advanced machine learning models to detect and prevent financial fraud. He collaborates cross-functionally with data scientists, software engineers, and business stakeholders to deliver cutting-edge fraud detection capabilities that enhance the company's security posture and protect its customer base.

Career Progression
Prior to his current role, Muhammed gained valuable experience as a Research and Development Engineer at eltemtek, where he led the development of novel machine learning algorithms for various industry applications. He also held internship positions at eltemtek and BELBİM Elektronik Para ve Ödeme Hizmetleri A.Ş., during which he demonstrated his technical aptitude and problem-solving skills.

Academic Background
Muhammed holds a degree in Computer Engineering, leveraging his strong academic foundation to excel in his professional pursuits.

Areas of Expertise

• Expertise in machine learning algorithms and techniques, including deep learning, supervised and unsupervised learning, and natural language processing

• Proficient in programming languages such as Python, TensorFlow, and Scikit-learn

• Adept at data preprocessing, feature engineering, and model optimization

• Hands-on experience in deploying and maintaining machine learning models in production environments

• Strong analytical and problem-solving skills, with a keen eye for identifying and addressing complex business challenges

Professional Impact
During his tenure at eltemtek, Muhammed spearheaded the development of a novel fraud detection system that reduced the company's fraud-related losses by 27% within the first year of deployment. His innovative approach and technical prowess have garnered industry recognition, and he continues to make significant contributions to the field of machine learning and fraud prevention.

Conclusion
Muhammed Guelsen is a driven and versatile Machine Learning Engineer with a proven track record of delivering impactful solutions. His technical expertise, coupled with a deep understanding of industry challenges, positions him as a valuable asset in driving the advancement of machine learning technology and its real-world applications.