Mark Lin

Baseball Analytics Associate

Shanghai, United States
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Summary

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Rockstar
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Mark Lin is a Baseball Analytics Associate with nine years of quantitative and applied-algorithm experience, currently shaping data-driven decision making for the Detroit Tigers. He blends an academic foundation in applied analytics from Columbia with practical baseball player development certification to turn complex models into actionable scouting and performance insights. His background spans interdisciplinary research in probabilistic programming and modular Bayesian inference as well as hands-on work building VBA tools, K-means clustering, and visual analyses to uncover hidden player patterns. Mark has contributed to the baseball analytics community via SABR, freelance writing, and conference presentations, demonstrating an ability to communicate technical findings to practitioners. Comfortable across research, consulting and product-facing roles, he pairs mathematical rigor with domain knowledge in sports science and economics. A multilingual, internationally trained analyst based in Shanghai, he brings both global perspective and a penchant for elegant, algorithmic solutions to baseball problems.
code9 years of coding experience
job1 year of employment as a software developer
bookCertificate, Baseball Player Development, Certificate, Baseball Player Development at Sports Management Worldwide
bookPostbaccalaureate Studies, General Studies, Postbaccalaureate Studies, General Studies at Columbia University in the City of New York
bookMathematics and Science Resources Class, Mathematics and Science, Mathematics and Science Resources Class, Mathematics and Science at National Chiayi Senior High School
bookBachelor of Business Administration - BBA, Business Economics; Minor in Korean Studies, Bachelor of Business Administration - BBA, Business Economics; Minor in Korean Studies at City University of Hong Kong
languagesEnglish, Chinese, Korean
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Github Skills (81)

python10
feature-engineering10
hyperparameter-optimization10
automl10
r10
sql10
neural-architecture-search10
spark10
data-science10
java10
automated-machine-learning10
keras-tensorflow10
machine-learning10
spark-ml9
mozilla-firefox9

Programming languages (5)

C++CoffeeScriptScalaJupyter NotebookPython

Github contributions (5)

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hibayesian/spark-fm

May 2017 - Jun 2020

Contributions:15 commits, 16 pushes, 1 branch in 3 years 1 month
hibayesian/spark-lof

May 2017 - Jan 2022

A parallel implementation of local outlier factor based on Spark
Contributions:5 commits, 1 PR, 4 pushes in 4 years 9 months
outlier-detectionparallelfactorspark-mlmachine-learning
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