Mikhail Kozine
About Mikhail Kozine
Mikhail Kozine is a Senior Data Science Architect at Harvard Business School, with extensive experience in data science and algorithm design. He has held significant roles at various companies, including Levi Strauss & Co. and Allstate, and has a strong academic background in mathematics and applied mathematics.
Current Role at Harvard Business School
Mikhail Kozine serves as a Senior Data Science Architect at Harvard Business School, a position he has held since 2023. His role involves leveraging advanced data science techniques to support various academic and administrative initiatives. He works remotely, allowing him to collaborate with a diverse team of professionals in the field of data science.
Previous Experience at Levi Strauss & Co.
Prior to his current position, Mikhail Kozine worked at Levi Strauss & Co. as the Lead Data Scientist from 2020 to 2023. During his tenure in the San Francisco Bay Area, he focused on designing and deploying machine learning models that contributed to significant business outcomes, showcasing his ability to apply data science in a retail context.
Educational Background in Mathematics
Mikhail Kozine has a strong educational foundation in mathematics. He studied at Moscow State University, where he earned a Master of Science degree from 1978 to 1984. He further pursued his academic interests at the Crystallography Institute of the Russian Academy of Sciences, where he has been working towards a PhD in Applied Mathematics since 1997.
Expertise in Data Science and Programming
Mikhail Kozine possesses extensive expertise in data science, particularly in algorithm design and systems control. He is well-versed in a variety of programming languages and tools, including Python, R, Spark, SQL, and C. Additionally, he has experience with cloud platforms such as Google Cloud Platform (GCP) and Amazon Web Services (AWS), which enhances his capabilities in deploying data-driven solutions.
Diverse Professional Experience
Mikhail Kozine has held various roles across multiple organizations, including Allstate, Applied Materials Inc., and Omnicell. His positions ranged from Principal Data Scientist to Advanced Process Control Baseline Manager. His experience spans predictive maintenance for industrial equipment and the application of deep learning techniques, indicating a broad and versatile skill set in data science.