DMITRII RYKUNOV: BRIDGING BUSINESS AND AI – A JOURNEY FROM DATA SCIENCE TO STRATEGIC INNOVATION

As Artificial Intelligence (AI) systems become more sophisticated, understanding how they make decisions (explainability) and ensuring those processes are transparent to users and stakeholders are increasingly challenging. This fact is crucial not only for building trust but also for meeting regulatory requirements. The industry is working on developing more explainable AI models and strategies for making complex AI systems understandable to non-experts. Dmitrii Rykunov, a top expert in Applied AI, is here to overcome the issues.

Mr. Rykunov, a Data Scientist and an expert in AI, possesses a deep blend of mathematical methods in Economics from the National Research University Higher School of Economics in Russia and Corporate and Organizational Strategy from the London School of Economics. His professionalism has already resulted in many successful AI transformations across various industries. Dmitrii’s work focuses on strategic project leadership, impact analysis, design, and implementation of AI-enabled solutions across multiple industries and use cases.

Thank you for joining us, Mr. Rykunov. Your career in the field of AI is impressive. What inspired you to start working in this sphere?

My journey into AI was unexpectedly sparked during the final year of my bachelor’s degree in economics in 2016/2017. A friend shared a link to a workshop at the Yandex headquarters, where a Google researcher discussed recent breakthroughs in image-captioning models. This workshop was my first real exposure to AI, and I was captivated. The technology seemed highly intuitive and opened my eyes to the potential of accomplishing tasks I had never considered possible with technology. This experience ignited a keen interest in AI, marking the beginning of my career path in this exciting field.

Great beginning! Right after graduation, you worked as a data scientist on multiple projects, achieving a 50% reduction in prediction errors compared to baseline solutions. What was the driving force to choose this way?

That’s a great question! Inspired by the intersection between technical and business skills in applied AI, I decided to pursue a career as a data scientist as I saw the potential for AI to solve complex business problems and transform industries, viewing it not just as a technological tool but as a transformative agent for society. My proactive outreach and motivation to bridge technical and business domains landed me a Data Scientist position at Yandex Data Factory (YDF). I gained hands-on experience and valuable learning opportunities that shaped my career. My fundamental background in economics and econometrics provided me with a unique advantage in planning and evaluating the economic impact of AI initiatives compared to specialists from purely mathematical disciplines. This multidisciplinary approach allowed me to participate in projects from strategy development to implementation, bridging the gap between different perspectives and contributing to more holistic project outcomes.

Mr. Rykunov, as a data scientist over the next several years, you significantly impacted the company’s productivity by launching an advertisement targeting solution that allowed you to increase marketing return on investment (ROI) by 25%. Can you share the challenges you faced during that time?

I developed a methodology to enhance online advertising targeting for Yandex.Afisha leveraging large datasets to assess the likelihood of a user purchasing a ticket after clicking on an ad. This approach addressed the challenge of inefficient advertising budget allocation, enabling more focused advertising toward users with a higher likelihood of purchasing. The methodology proved beneficial not only for Yandex.Afisha, but also for other online platforms seeking to improve the effectiveness of their advertising campaigns. The methodology could predict the purchase probability after ad clicks by utilizing machine learning to analyze user behavioral data and their history of interactions with the platform. This capability allowed for the automated optimization of advertising campaigns in real time, ultimately leading to increased ROI. Overcoming these challenges required a combination of technical expertise, collaboration, and innovative thinking. The result was a methodology that significantly improved the efficiency and effectiveness of online advertising campaigns.

Absolutely! Remarkable results with the market expansion reaching up to 70% of Russian internet users compared to the previous 40% demonstrate your high professionalism. Mr. Rykunov, what prompted you to transition to work as a consultant in the field of AI after achieving such incredible success?

My transition to work as a consultant was driven by a desire to apply my approach to data science and AI in a broader context that merged business acumen with technical expertise, a method I’ve personally developed and refined throughout my career, starting notably at my time with McKinsey & Company. This methodology is more than just a simple intersection of business strategy and data science. It’s about deeply understanding and translating the nuances of technical possibilities into tangible business outcomes, crafting innovative and practically implementable solutions. I recognized a significant need for this approach beyond big tech companies. Many projects in the field of AI needed to be better communicated and understood between technical teams and business stakeholders, leading to inefficiencies and solutions that were not aligned with long-term goals. I saw the opportunity to leverage my technical knowledge and economics background to bridge these two worlds, ensuring that AI solutions were technically feasible and strategically aligned with business objectives. Transitioning to work as a business analyst on projects with AI allowed me to apply this methodology to a broader range of business challenges, helping companies significantly improve their operations and creating new opportunities for growth and expansion.

Mr. Rykunov, the projects you led at McKinsey & Company propelled the adoption of AI solutions across the industry, setting new standards for customer management in retail and beyond. What plans do you have for the future?

In addition to my professional endeavors, I am passionate about creating innovative solutions using AI in various domains. I plan to establish an independent agency dedicated to helping companies implement cutting-edge AI solutions, from strategic planning to execution. Outside of work, I channel my creativity into a fashion brand where I use AI to design unique creations. Some of these designs have already been recognized and featured in Vogue, highlighting the intersection of technology and fashion. Another area of interest lies in developing adaptable personal virtual assistants driven by generative AI. I aim to create assistants integrated into users’ lives, offering personalized and proactive support.

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