Jhonsen Djajamuliadi
Senior Data Scientist
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolJhonsen Djajamuliadi is a Senior Data Scientist in Seattle with 11 years of experience applying computational science to real-world problems, bridging physical chemistry, high-performance simulation, and production ML/AI. Trained as a PhD physical chemist, he specializes in spectral data analysis, signal-to-noise separation, and large-scale molecular simulations run on supercomputers—skills he now translates into regression, classification, NLP, and computer vision solutions. At Trupanion and Microsoft engagements he has built and productionized ML and rule-based systems for automation and data quality remediation, collaborating closely with engineers to integrate models into product workflows. He is fluent in Python, PySpark, SQL, Airflow, Matlab and visualization tools, and has experience designing training data strategies and error-analysis tooling. Beyond models and code, Jhonsen is passionate about science communication and storytelling, distilling complex technical ideas for mixed audiences. An unconventional strength is his hands-on lab background—mammalian cell culture and spectroscopy—which gives him a practical intuition for noisy, experimental data pipelines.
11 years of coding experience
16 years of employment as a software developer
Associate of Arts - AA Liberal Arts and Sciences/Liberal Studies, Associate of Arts - AA Liberal Arts and Sciences/Liberal Studies at Windward Community CollegeDoctor of Philosophy - PhD Physical Chemistry, Doctor of Philosophy - PhD Physical Chemistry at University of Hawaii at Manoa
indonesian, english
Github Skills (19)
jupyterlab-extension10
jupyter9
widgets9
notebook9
jupyterlab9
ipywidgets9
jupyter-widget9
jupyter-notebook9
metis7
science5
python5
data-science4
machine-learning4
implicit4
data-analysis4
Programming languages (4)
Github contributions (5)
jhonsen/Coding365
Oct 2019 - Dec 2020
Contributions:168 commits, 150 pushes, 1 branch in 1 year 2 months
justinkuan/racial-bias-detection
Dec 2020 - Feb 2021
Racial-bias-detection is a research project on evaluating implicit bias in news media. We strive to use a data-oriented, functional design with a focus on end-to-end research productivity.
Contributions:44 commits, 7 PRs, 15 pushes in 2 months
pythonend-to-endimplicitproductivitymachine-learning
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