Mihhail Fjodorov
About Mihhail Fjodorov
Mihhail Fjodorov is a Machine Learning Engineer at Starling Bank in London, specializing in developing RESTful microservices and employing big data tools. He holds an MSc in Financial Economics and a BA in Banking and Finance from the University of Leicester.
Work at Starling Bank
Mihhail Fjodorov has been employed at Starling Bank as a Machine Learning Engineer since 2021. In this role, he focuses on developing and implementing machine learning models to enhance banking services. Prior to this position, he worked as a Data Engineer at the same organization from 2019 to 2021. His responsibilities included data manipulation and the application of machine learning techniques to improve data-driven decision-making processes.
Education and Expertise
Mihhail Fjodorov studied at the University of Leicester, where he earned a Master of Science in Financial Economics from 2012 to 2013. He also completed a Bachelor of Arts in Banking and Finance from 2008 to 2011. His educational background provides a strong foundation for his expertise in machine learning and data analysis. He specializes in developing RESTful microservices using Java, Python, and Go, and has experience with big data tools such as Apache Spark and Apache Flink.
Technical Skills
Mihhail Fjodorov possesses a range of technical skills relevant to his role as a Machine Learning Engineer. He works with concurrency models in Java and Python, utilizing frameworks such as Akka actors and Pykka Actors. His proficiency includes data manipulation and machine learning libraries like numpy, pandas, and scikit-learn. Additionally, he has experience with application monitoring tools, specifically JMX and Jolokia.
Previous Experience
Before joining Starling Bank, Mihhail Fjodorov worked as a Quantitative Analyst at Admiral Markets Group from 2014 to 2015 in Estonia. This role involved analyzing financial data and developing quantitative models to support trading strategies. His diverse experience in both engineering and analysis has contributed to his current capabilities in machine learning and data engineering.