
Vitalii Dodonov
Co-founder and CTO at Stan, empowering creators to become entrepreneurs
Toronto, Ontario, Canada
Summary
Vitalii Dodonov is a driven entrepreneur and engineer who co-founded Stan, a platform designed to empower creators to build and monetize their businesses. He leads Stan's engineering as CTO, contributing to its rapid growth and focus on leveraging AI to support the creator economy. His journey into entrepreneurship was fueled by early side projects, including Vhinny, which laid technical groundwork for Stan's current offerings. sacra+4
With a strong background in data science and software engineering, Vitalii has a proven track record of designing and implementing complex systems. His experience at Deloitte as a Data Scientist and at eBay as a Senior Software Engineer provided him with valuable skills in backend development, data processing, and front-end design, which he applied directly to building Vhinny.com and subsequently Stan. theorg+1
Vitalii is also a prolific writer on topics related to investing, data science, and entrepreneurship, sharing insights on platforms like Medium. His articles demonstrate a deep understanding of market analysis, machine learning applications, and the strategic aspects of building and scaling engineering teams in startups. This showcases his commitment to not only building but also sharing knowledge within his field. medium+5
Work
Education
Writing
Founding An Engineering Team at an Early Stage Startup
January 1, 2021A definitive guide on hiring junior and senior talent for a startup.
On How Elite is Mediocre
March 1, 2020An article summarizing why individual investors often have better chances of beating the market compared to financial institutions.
Effect of Financial Statement Release on Stock Prices
January 1, 2019A study analyzing the stock price behavior at the time when US companies file their earnings with the SEC.
How Many Industries are There?
January 1, 2019Predicting the Stock Market with Machine Learning. Drivers.
January 1, 2019Describes the drivers of a machine learning model for stock market prediction.