Slava Nikitin is a data scientist and machine learning practitioner with 11 years of experience building production-grade AI systems that turn statistical rigor into business impact. He currently improves last-mile logistics at DoorDash and previously led a cross-functional team at Covail to ship an Attack Detector Solution that cut cyber detection times from hours to seconds while slashing false positives. Slava combines deep probabilistic modeling and Bayesian approaches with hands-on engineering—R and Python packages, cloud pipelines, ELK, and Docker—to move projects from prototype to paying customers. He has applied these skills across healthcare, finance, utilities and science, delivering quantile forests, copula models, sequence-to-sequence text models and hierarchical Bayesian solutions. An educator and mentor, he taught MBA students to translate data into actionable business decisions and has mentored dozens of data scientists. Based in Chicago, he blends quantitative psychology and mathematical statistics training with product-minded execution, and is actively developing ADS at covail.com/attack-detector-solution.
11 years of coding experience
6 years of employment as a software developer
Bachelor’s Degree, Psychology, Neuroscience (minor), Philosophy (minor), Bachelor’s Degree, Psychology, Neuroscience (minor), Philosophy (minor) at Loyola University Chicago
Master’s Degree, Quantitative Psychology, Master’s Degree, Quantitative Psychology at The Ohio State University
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