Michael K is a software engineer in New York with 11 years of experience building production ML, NLP, and big-data infrastructure for finance and consumer companies. He has delivered models for optimal order matching, pairs trading, trade cost prediction, and architected alternative-data pipelines (POS, image recognition, ESG) used by discretionary and systematic investors. Comfortable across cloud environments and languages (Python, C++, Scala, Spark, TensorFlow) he blends quant trading expertise—especially fixed income and interest rates—with hands-on systems work like Kubernetes and server development. A former distressed-investment analyst and derivatives modeler, he pairs an MBA from Michigan with deep technical masters’ training, enabling him to translate complex financial research into robust, self-serve engineering platforms. Notably, he’s managed teams up to 14 and has been programming since 2001, bringing reverse-engineering instincts to production-grade analytics.
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