Welcome to another installment of Arbol's Expert Insights series!
Igor Stankevich is the Managing Director of Climate Risk at Arbol, leading a team focused on Machine Learning models and risk development. Integral to his work are advanced APIs and internal and external pricing tools which are supported by a robust cloud infrastructure.
Q: You have over 20 years of software development experience and a background in AI, finance, and commodities. How do you believe your professional experience has influenced your role at Arbol?
Q: Caching is one of the toughest problems in computer science. Can you explain, in layperson's terms, how you overcame natural bottlenecks in the system to keep things scalable?
Q: Insurance and risk management depend on accurate data. How does Arbol's approach to data management stand out?
Q: Please tell us about your ongoing interest in Diffusion and Consistency models. For the benefit of our readers, can you unpack these concepts and explain why they're essential to today's risk management landscape?
Q: Given the rapid evolution of technology and its intersection with risk management, where do you see the industry's future going?
Q: You recently attended the International Conference on Machine Learning. Were there any key takeaways or insights from the conference that you hope to implement at Arbol in the near future?
Q: Lastly, for young professionals looking to delve into the intersection of tech, data, and risk management, what advice would you give them?
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