Wendy Wang
Hedge Fund Research Associate
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolWendy Wang is a Hedge Fund Research Associate in New York with a decade of experience across investment analysis, operations, and private equity, currently at HSBC after five years at Superstring Capital. She combines a rigorous academic foundation—MS in Data Analytics and a MA in Political Economy—with hands-on quantitative skills, having implemented classical ML algorithms (perceptron, k-NN, Naive Bayes, logistic regression, AdaBoost) for MNIST in her GitHub project. Comfortable at the intersection of finance and data science, Wendy has supported TMT and healthcare investments and brings operational discipline from family-office and advisory roles. Her portfolio reflects both macro research experience (Brookings, UNDP) and practical algorithmic experimentation, suggesting a blend of strategic insight and technical curiosity. Notably, she pairs linguistic and economic training from Peking University with applied analytics from Zicklin, enabling clear communication of complex quantitative ideas.
10 years of coding experience
Exchange Program Business, Exchange Program Business at University of California, Berkeley, Haas School of BusinessShanghai High SchoolBachelor of Arts - BA Linguistics / Economics, Bachelor of Arts - BA Linguistics / Economics at Peking UniversityMaster's degree Political Economy, Master's degree Political Economy at Duke UniversityMaster of Science in Data Analytics, Master of Science in Data Analytics at Zicklin School of Business
Chinese, Shanghainese, English, Spanish
Github Skills (17)
algorithm10
algorithms10
opencv10
python10
scikit10
machine-learning10
implement10
mnist10
scikit-learn10
data-analysis10
adaboost9
naive-bayes9
perceptron9
knn9
logistic-regression9
Programming languages (2)
Github contributions (5)
WenDesi/lihang_book_algorithm
Jul 2016 - Jul 2017
致力于将李航博士《统计学习方法》一书中所有算法实现一遍
Role in this project:
ML Engineer
ML EngineerContributions:34 commits, 29 pushes, 1 branch in 1 year
Contributions summary:Wendy contributed significantly to implementing and experimenting with various machine learning algorithms, specifically for digit classification using the MNIST dataset. Their work involved developing and refining algorithms such as perceptron, k-NN, Naive Bayes, decision tree, maximum entropy, logistic regression, and AdaBoost. The commits demonstrate a focus on building, training, and evaluating these models, utilizing Python and libraries like pandas, scikit-learn, and OpenCV for feature extraction and model assessment.
pythonmachine-learning
WenDesi/AcfunFakeDriver
Jun 2016 - Dec 2022
Contributions:10 pushes, 1 branch in 6 years 6 months
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