Summary
Sergej Sizov is a data science and machine learning leader with 11+ years of experience building and scaling data ecosystems across academia and industry, now serving as a professor at Hochschule Koblenz. He has led and delivered 40+ data products and assets—several projects he managed independently had budgets of €3–8M—spanning data analytics, AI, data warehousing, semantic technologies and big data. Previously he created enterprise Data & Analytics organizations and an "AI Superpower" excellence initiative at Capgemini Invent, and architected consolidated data platforms at Thieme and PwC. Trained as a Dr.-Ing. in databases and an applied-math Diplom-Ingenieur, he blends deep research roots (Max Planck, multiple university professorships) with hands-on software engineering, load-testing and systems performance expertise. He is known for tackling complex, interdisciplinary data challenges and for motivating teams through tailored technical and personal development.
11 years of coding experience
2 years of employment as a software developer
Diplom-Ingenieur, Applied Mathematics, 1.0, Diplom-Ingenieur, Applied Mathematics, 1.0 at Technische Universität St. Petersburg
Dr.-Ing, Datenbanken und Informationssysteme, Magna Cum Laude (sehr gut), Dr.-Ing, Datenbanken und Informationssysteme, Magna Cum Laude (sehr gut) at Universität des Saarlandes