Detailed problem analysis, excellent market research, and software development are a few roles Dmitry Katunin performs in his professional career. Katunin has been the core contributor to a famous real estate market research program. He has also been a juror for the international Best Business Award 2022. With more than ten years of web and mobile solution development, Dmitry is an expert in his field and contributes to the success of InvestorLift, his current company, and the industry.
Originally from Bryansk, Russia, Dmitry Katunin is a software developer currently leading the group at InvestorLift responsible for introducing artificial intelligence to the system that will elevate InvestorLift's core research program God Mode. It is a commendable and the most recognized contribution by Katunin to his field. With his extensive contributions to God Mode, Katunin is responsible for introducing a comprehensive platform for buying and selling illiquid real estate in the US market for investment purposes.
InvestorLift aims to make the home purchase process seamless for buyers and wholesalers. One of the features introduced by Katunin involves details about the property on sale when the property is listed by the wholesaler. A notable feature of the platform is its 'Hot Buyers' section offering information about buyers who interacted with your property. The platform ranks these buyers per their level of interest using an action score. This feature also allows wholesalers to interact with buyers through the InvestorLift platform. The user-friendly platform featuring property and buyer databases across the United States and facilitating transactions between real estate sellers and wholesale buyers, as of 2019, reports $1.9 billion in annual sales.
Katunin responsible for the platform's real estate market research program God Mode, has increased Investor Lift's revenue by 500% in one year. As a specialist in his field, his contributions directly influence the company's growth. As a core developer of God Mode, Katunin contributes to its user interface logic development using JavaScript. The introduction of God Mode has made the platform intuitive. Users do not need to scroll through the property list. They can scroll on the property region and see the updated prices. Through God Mode, users can seamlessly check the average purchase and sale price and other property and owner details. Dmitry's work for InvestorLift's God Mode and revenue growth also led to the onboarding of more than a thousand new partners, including world-renowned celebrities like Cody Sperber, David Olds, and Nick Perry.
He is also responsible for developing the software architecture of the InvestorLift website and mobile application and works with databases. Being a specialist in his field and his role as a consultant, he was a juror for the international Best Business Award 2022. He reviewed more than 300 entries based on criteria like market relevance, the relevance of the software solution stack, fault tolerance of the solutions, and audience assessment. Along with the entry evaluation, Katunin also offered feedback to the participants and shared his experiences. He also offered advice on career opportunities in the field.
Katunin has also developed detailed and elaborate real estate analytics models and has also helped InvestorLift. These models are based on the classical methods of statistical analysis and actively implement machine learning algorithms to obtain effective results. Dmitry's models also have parameters based on indirect data.
Katunin's colleagues commend his deep programming knowledge, methodology, and analytical skills. They also admire his teaching skills, empathy, and responsible nature. According to InvestorLift CEO Robert Wensley, "Dmitry Katunin represents a class of young engineers utilizing modern machine learning practices instead of cumbersome high-loaded mathematical calculations that can give false positives in practice. I am delighted to have the opportunity to work with him and to share the joy of his success in developing models for big data analysis."
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