Financial Analyst Data

YINGZHI WANG

*** **** ******, *** ****, NY, ***** C: 929-***-**** ******@***.***

EDUCATION

New York University, Tandon School of Engineering 09/16 - 05/18 Master of Science in Finance Engineering, Computational Finance GPA: 3.7/4.0

Sun Yat-Sen University 09/12 - 06/16

Bachelor of Science in Mathematics and Statistics

GPA: 3.7/4.0

SKILLS & COURSEWORK

● Programming Skills: Python, R, MATLAB, SQL, Excel VBA, Bash, STATA, SAS, C++, LaTeX

● Modeling and Analysis: Financial Econometrics, Algorithm and Data Structure, Data Visualization

● Math and Statistics: Machine Learning, Probability and Statistics, Stochastic Calculus, Optimization and Linear Algebra

PROFESSIONAL EXPERIENCE

Data Assistant, NYU Wagner Graduate School of Public Service, NY 09/17 – 05/17

● Architected an effective way using AWS Lambda and SNS storing webform data into S3 for backup and security improvement.

● Apply machine learning classification on program applicant web survey data to focus on how different environment and background factors of candidate impact the application result based on Python sklearn.

● Salesforce: Create new contact information objects and improve efficiency of data management more than 50%; queried, cleaned and analyzed students’ academic data and visualize degree enrollment distribution of students in Python for Program Team to make management decisions; build solution on duplicate accounts with Python fuzzywuzzy.

● Collaborate with colleagues over inspecting Eventbrite registration errors and provide faculties assistance through ServiceLink.

Financial Analyst, PrimeAlpha, NY 06/17 - 10/17

● Construct a Excel VBA model to accurately collect and update daily and weekly financial data (net returns and AUMs) efficiently with accuracy improved 90% from clients’ financial reports.

● Conducted quantitative and qualitative research through about 30 investment funds in the real estate space under Bloomberg terminal; conclude key characteristics of the funds and main factor attribution of stock indexes using Machine Learning PCA method.

● Maintained well organized, extensive, and up-to-date due diligence documentation on hedge funds with average AUM of 500MM, testing, and verification/quality control documents and programs in compliance with company and clients standards.

● Evaluated investment funds based on strategy, opportunity set, investment process, risk and portfolio management, and fee structure.

Data Researcher, Teaching Assistant, Dataguru, CN 06/15 - 05/16

● Developed a prediction model for course opening situation and student involvement in R using Logistic Regression and SVM method; improved the questionnaire for investigating potential learner’s interests on the opening online courses.

● Created my own online courses on the Dataguru website relative to the application of basic statistics knowledge using STATA.

● Evaluated and instructed online candidate performance and provided solutions in data analysis courses (SPSS, SAS, Excel VBA, etc.).

● Organized the development and implementation of daily, weekly or long-range strategic preventive, predictive and scheduled curriculum plans.

PROJECTS

Course Projects (Python) - Applied Machine Learning, NYU 02/18 - 05/18

● Investigated breast cancer data to classify between malignant or benign by contributing variables using Decision Trees and measured conditional probabilities; visualized and compared the the results before and after prone the trees.

● Built a Bayesian Network in order to analyze the probability of student suicide based on different factors, using public database.

● Analyze bankruptcy data using Classification Tree and improve accuracy using Bagging (Bagged Decision Tree, Random Forest, Extra Tree) and Boosting (AdaBoost, Stochastic Gradient Boosting Classification); select method is Voting Ensemble.

Factor Attribution (Python) - Capstone Project, NYU & ETF Global 09/17 - 12/17

● Build and compare regression models on Fama-French, AQR and MSCI Indexes datasets to understand ETFs’ factor attribution including OLS, Polynomial, Stepwise, Ridge, Lasso, ElasticNet, Bayesian Linear Regression.

Coursework and Project (R) - Financial Econometrics, NYU 0 2/17

● Do research and simulation on models like method of moments, maximum likelihood estimation, Bayesian estimation, least-squares estimation, robust estimation, kernel estimation and multiple regression, logistic regression and time series estimation.

● Project on newly discovered properties of cointegrated time series to design and improve an active trading strategy.

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