Summary
Natalia Timakova is a data analyst with a decade of cross-disciplinary experience applying analytics and product insight to EdTech, journalism, wikis, retail AI and fintech. Currently at Google and mentoring at Pathrise, she blends rigorous ML-oriented analysis with product sensibility to improve user trust and outcomes—most notably uncovering a labeling bug at Wikimedia that boosted classifier AUC from 90.9% to 92.8%. Her background as an investigative journalist and editor for energy markets informs a knack for turning messy, real-world data into clear, actionable narratives for executives and engineers alike. Comfortable with Python, SQL, YAML/JSON and visualization, she has delivered solutions ranging from grocery-sales elasticity models to hedge-fund reporting and AI-assisted consumer features. Based in Mountain View with a Master’s from UC Berkeley School of Information, she is especially driven by products that advance education, independent media, and knowledge sharing.
10 years of coding experience
3 years of employment as a software developer
Master’s Degree, Information Technology, 3.78, Master’s Degree, Information Technology, 3.78 at UC Berkeley School of Information
General Studies: Science, 3.85, General Studies: Science, 3.85 at Foothill College
Associate's degree, Major: Structure, historical development, and relationships of languages; Minor: Teaching, Associate's degree, Major: Structure, historical development, and relationships of languages; Minor: Teaching at Sakhalin State University
BA, MA, Journalism, with honors, BA, MA, Journalism, with honors at Russian State Social University (former Moscow State Social University)