Kha Nguyen
Data Engineer
Vantaa, Finland
Summary
👤
Senior🎓
Top SchoolKha Nguyen is a versatile data engineer and machine learning practitioner with 11 years of experience building production-ready software and data solutions across startups and global firms. His background spans computer vision and medical data, time-series forecasting, and customer data science, with earlier roles contributing to software at Microsoft, T-Mobile and genome research labs. Comfortable across backend, frontend and databases, he bridges research and engineering—having worked on self-driving car projects and protein/DNA sequencing tools—so he thrives where complex data meets scalable systems. Based in Vantaa, Finland, he combines consultancy experience at Futurice and Reaktor with an Aalto master’s in Machine Learning and hands-on engineering discipline from UW, enabling rapid prototyping that moves models into production. An often-overlooked strength is his ability to translate domain research (e.g., mass-spectra migration and missed-cleavage analysis) into maintainable engineering deliverables.
11 years of coding experience
11 years of employment as a software developer
B.S, Computer Engineering, Computer Engineering, B.S, Computer Engineering, Computer Engineering at University of WashingtonMaster's degree, Machine Learning and Data Science, Master's degree, Machine Learning and Data Science at Aalto UniversityAS, Computer Science, AS, Computer Science at Seattle Central College
Vietnamese, English
Github Skills (200)
neural-network10
amazon10
scraper10
time-series10
forecasting10
multiprocessing10
anomaly-detection10
python10
prophet10
node-red10
memoization10
machine-learning10
gpu10
forecast10
caching10
Programming languages (17)
Github contributions (5)
khanetor/blockipedia-near
Jan 2022 - Jul 2022
A wikipedia on NEAR Protocol blockchain
Contributions:25 reviews, 53 commits, 50 PRs in 5 months
blockchain-platformblockchainblockchain-protocolplutussubgraph
khanetor/dropout-in-rnn
Jan 2020 - Jun 2020
This is my master thesis project. The goal is to apply dropout within RNN in order to obtain uncertainty for predictions.
Contributions:32 commits, 4 PRs, 7 pushes in 4 months
rnngoaldeep-learningmastermachine-learning
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