Maria Fabiano is a Senior Data Scientist with nine years of experience blending applied machine learning, NLP, and large-scale data engineering to solve entity resolution and record linkage challenges. Currently pursuing an MS in Computer Science at UT Austin, she combines academic research in language-grounded reinforcement learning with production experience at Ancestry, where she led a team that linked 70 million historical records using Spark, AWS, and XGBoost. Her background includes industry internships at Google and Palo Alto Networks, where she built web-scraping pipelines, BERT-based classifiers, and high-performing customer-prediction models. Comfortable moving models from research to production, she has a track record of measurable impact (e.g., 60% linkage rate at 98% confidence and an 81% ROC AUC model) and a knack for translating messy, real-world data into reliable ML systems.
9 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at The University of Texas at Austin
Bachelor of Science - BS, Computational and Applied Mathematics, Bachelor of Science - BS, Computational and Applied Mathematics at Brigham Young University
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