Marina Zavalina
Machine Learning Engineer at Google
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolMarina Zavalina is a Machine Learning Engineer at Google with eight years of experience applying ML to ranking, NLP, time series, and broader data science problems. She combines rigorous academic training (MS in Data Science from NYU and strong economics/math foundations) with hands-on product experience across finance, research, and enterprise settings including JPMorgan, IBM, and Hypergiant. Her work spans end-to-end ML—from semi-supervised NLP classifiers to satellite-based PM2.5 estimation—and she is comfortable taking models from research prototypes to production. An experienced educator, Marina has over five years of teaching and TA experience, which she leverages to clearly communicate complex concepts like game-theoretic equilibria and advanced mathematical ideas. Based in the NYC area, she programs primarily in Python and PyTorch and brings a rare blend of pedagogical clarity and production-grade ML engineering.
8 years of coding experience
2 years of employment as a software developer
Mathematics, Mathematics at Moscow State School 57Bachelor's degree, Economics, 8.9 / 10.0, Bachelor's degree, Economics, 8.9 / 10.0 at Higher School of EconomicsBachelor's degree, Economics, 8.9 / 10.0, Bachelor's degree, Economics, 8.9 / 10.0 at New Economic SchoolMaster of Science - MS, Data Science, Master of Science - MS, Data Science at New York UniversityBachelor's degree, Agricultural Economics, Bachelor's degree, Agricultural Economics at Universitat Pompeu Fabra
English, Russian, Spanish
Github Skills (20)
satellite-images9
satellite8
capstone7
supervised-learning7
computer-vision6
jupyter-notebook6
science6
self-supervised-learning6
ipython6
dialogue-systems5
machine-learning5
wikipedia5
python5
parser5
pytorch4
Programming languages (2)
Github contributions (5)
mmarinated/ssl_project
Apr 2020 - May 2020
Final project on self-supervised learning for DL course
Contributions:43 commits, 2 PRs, 5 pushes in 1 month
pytorchsupervised-learningsuperviseddeep-learningmachine-learning
peeyushster/Semantic-Segmentation-of-Geospatial-Images
Nov 2018 - Mar 2019
Identifying point-of-interests within satellite images
Contributions:17 commits, 5 PRs, 9 pushes in 3 months
satellitesatellite-imagescomputer-visionpointinterests
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