Deepu Komati is a dynamic Data Scientist and Engineer with experience transforming complex business challenges through advanced analytics solutions. As a Lead Engineer at PenFed Credit Union, Deepu spearheads fraud detection systems that have reduced payment fraud, saving approximately millions annually.
With expertise spanning machine learning, data engineering, and predictive analytics, Deepu has a proven track record of delivering measurable outcomes across financial services, e-commerce, and cloud security industries. His innovative work includes developing machine learning models that improved collections recovery rates and optimizing recommendation systems that boosted e-commerce sales.
Deepu combines technical mastery in Python, AWS, and Salesforce ecosystems with strategic insights that drive business value. His implementation of automated threat detection systems at Amazon AWS Security reduced threat response time, while his data-driven approaches at Flipkart increased customer retention and conversion rates significantly.
A graduate of George Mason University with a Master's in Data Analytics Engineering, Deepu is passionate about leveraging artificial intelligence to solve real-world problems. He specializes in fraud detection, customer segmentation, and recommendation systems that enhance both operational efficiency and customer experience.
Beyond technical implementation, Deepu excels at cross-functional collaboration and translating complex data concepts into actionable business strategies. His work at Capital One building machine learning models achieved high accuracy in fraud detection while reducing false positives, demonstrating his ability to balance precision with operational efficiency. Deepu's approach combines cutting-edge algorithms with pragmatic business acumen, making him adept at communicating technical solutions to both technical and non-technical stakeholders.