M Asyrofi
Data Scientist
Singapore
Summary
👤
Senior🎓
Top SchoolM Asyrofi is a data scientist and machine learning engineer based in Singapore with 9 years of experience building production ML systems and leading cross-functional teams. He has delivered high-impact products—from AVMs and address-matching pipelines at PropertyGuru that corrected 150k listings and unlocked six-figure revenue improvements, to search-by-image and OCR features at Bukalapak. A former AI research engineer, he published first-author work in IEEE Transactions on Software Engineering and maintains hands-on expertise with PyTorch, TensorFlow, Docker, and AWS. He also co-founded a startup (CTO) that won multiple competitions and secured investment, demonstrating both technical depth and entrepreneurial drive. As an AWS Community Builder, Kaggle Expert and certified AI Solutions Architect, he blends research rigor with practical deployment experience to turn complex data into reliable, revenue-driving products.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science, 3.68 / 4 | Cumlaude, Bachelor of Engineering - BE, Computer Science, 3.68 / 4 | Cumlaude at Institut Teknologi BandungSummer School Student, Big Data in Society, 8.5 / 10, Summer School Student, Big Data in Society, 8.5 / 10 at Vrije Universiteit Amsterdam (VU Amsterdam)
English, Indonesian
Stackoverflow
21reputation
4kreached
1answer
0questions
Github Skills (94)
code-search-engine10
todoist9
sentiment9
istanbul8
voice8
api8
sentiment-analysis8
self-supervised-learning8
code-search8
speech8
coverage8
voice-recognition8
speaker8
keyword8
meilisearch8
Programming languages (6)
Github contributions (5)
mhilmiasyrofi/mhilmiasyrofi
Mar 2021 - Apr 2025
Contributions:20 PRs, 23 pushes, 20 branches in 4 years
soarsmu/BiasFinder
Jun 2020 - Jan 2022
BiasFinder: Uncovering Bias in Sentiment Analysis Systems through Metamorphic Testing
Contributions:320 commits, 1 PR, 35 pushes in 1 year 7 months
nlptestingmetamorphicsentimentbias
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