Solid mathematical skills in multivariate calculus and linear algebra.
Strong statistical knowledge regarding various topics, such as Probability Theories, Regression Analysis, Hypothesis Testing,
Survival Analysis, Statistical Inference, Computational Statistics, Data Visualizations and so on.
Proficient in many useful statistical programming languages, including R, SAS, MATLAB.
- Computer Science:
- Machine Learning:
Solid foundamentals in various machine learning methods. Experience of building machine learning models from scretch, without
applying popular ML toolkits. Wide exposure to Deep Learning methods, especially in Deep reinforcement learning. Proficiency in ML toolkits, such as Scikit-Learn, Keras, Pytorch.
Wide exposure to various topics, including Fixed Income Securities, Financial Derivatives, International Financial Management, Accounting, Equity Valuation, Econometrics and so on. Proficient in Excel VBA, STATA, SPSS. Participate in many case competitions.