Tal Galfsky

Staff Machine Learning Engineer at Altos Labs

New York, New York, United States
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Summary

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Tal Galfsky is a Staff Machine Learning Engineer in New York with six years of experience bridging advanced physics research and applied data science. He transitioned from a Ph.D. in nanophotonics and senior photonics engineering roles into data science at Cherre, where he built production-ready ML solutions for large-scale real estate data before moving to Altos Labs. Tal combines deep experimental optics expertise with practical ML and engineering instincts, enabling him to tackle noisy, multi-source datasets and deploy robust models. His background negotiating high-stakes contracts and improving logistics processes hints at strong stakeholder management and operational rigor beyond pure engineering. Colleagues can expect a practitioner who blends academic rigor, hands-on instrumentation experience, and production ML delivery.
code6 years of coding experience
job7 years of employment as a software developer
bookDoctor of Philosophy (Ph.D.) - Expected in Oct 2016, Physics - nanophotonics, 3.8, Doctor of Philosophy (Ph.D.) - Expected in Oct 2016, Physics - nanophotonics, 3.8 at The Graduate Center, City University of New York
bookBachelor of Science (B.Sc), Physics, 3.5, Bachelor of Science (B.Sc), Physics, 3.5 at Bar-Ilan University
languagesHebrew, English, German
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Stackoverflow

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Github Skills (11)

gcp9
google-cloud9
google-cloud-platform9
transform7
data-modeling6
slack6
analytics5
dbt4
sql4
elt2
business-intelligence1

Programming languages (2)

Jupyter NotebookPython

Github contributions (2)

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Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Contributions:1 review in 1 day
gcpgoogle-cloud-platformgoogle-cloudtraining
dbt-labs/dbt-core

Nov 2019 - Nov 2019

dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Contributions:1 issue in 1 day
analyticsdbt-viewpointtransformanalystssql
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