Summary
Alisa Zhila is a Data Scientist with a decade of experience building applied AI/ML systems for e-commerce, search, and conversational QA across leading tech companies. She has designed end-to-end evaluation frameworks and productionized models—ranging from multilingual RoBERTa-based answer quality predictors in Alexa to CNN classifiers that recover null-search results at Target. At Amazon she led query understanding efforts, creating multilingual evaluation pipelines for conversational signal and brand detection that directly informed production improvements. Her background bridges rigorous NLP research (PhD in NLP) and hands-on engineering, with early work in vision and fact extraction at IBM and practical NLP internships at Microsoft, Yahoo, and Oracle. Based in California, she combines deep error-analysis and data-centric iteration with scalable deployment experience across seven-plus locales. Less obvious: she pairs semantic-clustering approaches from computer vision with NLP evaluation design, yielding cross-modal insights that improve model robustness.
10 years of coding experience
6 years of employment as a software developer
Computer Science, certificates with honors, Computer Science, certificates with honors at Coursera
The National Polytechnic Institute of Mexico
Computer Science, Computer Science at Udacity
MS, applied phys and maths, MS, applied phys and maths at Moscow Institute of Physics and Technology (State University) (MIPT)
1416
English, Russian, Spanish, German