Nikita Iserson is a Lead Machine Learning Engineer at S&P Global with more than 10 years of experience spanning software engineering, data warehouse development, data analytics, and machine learning. That breadth matters in his work: building machine learning systems that hold up in production requires understanding not just the models, but the engineering and data infrastructure underneath them.

Over his career, Nikita has built demand forecasting systems, network analyses, recommender systems, digital twins, and much more. His projects cover a wide range of industries, including telecom, retail, and banking, which has given him a practical sense for how the same modeling techniques translate into very different business contexts and constraints.

In his current role at S&P Global, Nikita leads machine learning engineering efforts, combining his analytical depth with the discipline of a software engineer. He is particularly interested in taking ML projects from prototype to reliable production systems that deliver measurable business value.