Zelin Chen

Background

About Zelin Chen

Who I am I am a Quantitative discipline graduate from the University of Melbourne. I have a hardcore of economic data analytics skills with continuous improvement and problem-solving attitude. Skills and Competencies - Competent in programming large data science projects in R. Also familiar with popular data science programming languages, e.g. Python, Matlab, Stata and EViews- Familiar with both major econometric and machine learning models. Including but not limited to-> Econometrics: OLS, GLS, probit, logit, ARIMA, GARCH, M-GARCH, Kalman Filters, PCA, Bayesian analysis-> Machine learning: ANN, CNN, RNN, SVM, Multi-armed Bandit, Gaussian Mixture model- Communication skills in explaining complex quantitative models to stakeholders with various professional backgrounds. Key experience - Developed genetic programming based FOREX trading strategy searching algorithm and published on GitHub- As a team, helped WSP ANZ to discover its business opportunities in Machine learning and produced an internal report addressing four primary opportunities that WSP should consider- Tutored Master of Finance students in Quantitative Analysis of Finance II subject and received 4.4/5 student rating overall- As a team participated in Melbourne Business School Student Association Case Competition producing business case analysis for Ericsson and Accenture and earned second place in the end. Awards - Graduate Dean's Honours List - A.G. Whitlam International Graduate Merit Scholarship