Khuyen Tran - CEO at CodeCut

Khuyen Tran

CEO at CodeCut

Hayward, California, United States

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Summary

🤩

Rockstar

🎓

Top School

Khuyen Tran is a CEO and senior data engineer with six years of experience building MLOps and developer-focused data platforms from the Bay Area. As founder of CodeCut and Developer Advocate at Nixtla, Khuyen creates accessible data science content that reaches over 100,000 monthly readers while helping teams adopt robust pipelines. Hands-on accomplishments include designing ingestion workflows that moved 50+ million records into S3, building end-to-end SageMaker MLOps pipelines, and improving developer experience at Prefect to increase reliability and reduce development time. An active open-source contributor, Khuyen added backtesting and plotting features to the fastquant project and maintains a Data-science repo with practical notebooks like a LinkedIn message analysis that showcase reproducible toolchains. With a 4.0 BS in Statistics, a background in academic research and tutoring, and a track record of shipping well-tested Python code, Khuyen blends rigorous quantitative training with effective teaching and product-oriented engineering.

6 years of coding experience

6 years of employment as a software developer

4.0, 4.0 at Southern Illinois University Edwardsville

English, Vietnamese

Github Skills (15)

data-visualizations10

pandas10

machine-learning10

jupyter-notebook10

data-visualization10

data-visualisation10

tradingview10

backtesting10

python10

trading10

quantitative-finance10

backtest10

data-analysis10

data-science9

algotrading9

Programming languages (14)

SmartyMDXVueGoSassHTMLJupyter NotebookHCL

Github contributions (5)

khuyentran1401/Data-science

Jul 2020 - Jan 2023

Collection of useful data science topics along with articles, videos, and code

Role in this project:

Data Scientist

Contributions:627 commits, 7 PRs, 527 pushes in 2 years 6 months

Contributions summary:Khuyen implemented a message analysis feature using the pandas and Jupyter libraries, as evidenced by the creation of a `linkedin_analysis` directory containing an .ipynb file, `message_analysis.ipynb`, which loads and analyzes LinkedIn messages. They also uploaded files and created notebooks demonstrating the utilization of a suite of data science tools to solve tasks, showing hands-on understanding of the toolchains, including Data Science, Machine Learning and Data Visualization.

data-analysispythonsciencedata-sciencedeep-learning

enzoampil/fastquant

Dec 2020 - Jan 2021

fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!

Role in this project:

Back-end Developer

Contributions:11 commits, 5 PRs, 3 comments in 12 days

Contributions summary:Khuyen primarily contributed to the backtesting and strategy implementation aspects of the fastquant project. They added functionality for plotting backtest results, updated documentation, and made enhancements to existing trading strategies, specifically the MACD and RSI strategies, including features like upper and lower bands for RSI. Their changes also focused on refining the backtesting framework to incorporate more flexible plot arguments and improved functionality.

pythonfinancestocksalgorithmic-tradinglines

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