Michael is a data scientist with a deep understanding of machine learning algorithms and their applications. He focuses on developing custom monitoring solutions tailored to each client’s unique needs. His work involves continuous audits and real-time drift tracking, ensuring that clients can detect issues before they escalate. Michael believes that data is the backbone of successful AI implementation, and he is dedicated to empowering businesses through enhanced data-driven decision-making. In his free time, he enjoys coding and contributing to open-source projects.