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Data analyst, Data Scientist, Python Developer

Somerset, NJ, 08873
January 14, 2020

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** ***** ******,

Somerset, NJ 08873




RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY New Brunswick, NJ Rutgers Business School 09/2018 ~ 12/2019

Master of Information Technology GPA:3.62

Wuhan University of Science and Technology 09/2012 ~ 12/2016 Bachelor of Management Sciences GPA:3.5

Technical Skills

Technical Skills:Python, SPSS, Linux, SQL, MongoDB, ACCESS, MySQL Projects

Recommender system for amazon products 01/2019 ~ 05/2019

used collaborative filtering algorithms, deep learning and graph-based methods to build a recommender system for amazon products.

a matrix factorization method named singular value decomposition and stochastic gradient descent are applied.

Restricted Boltzmann Machine is applied to recommends items by trying to find users that are similar to each other based on their item ratings.

personalized PageRank algorithm is applied to calculate the similarity between products. Web-based Stock Forecaster 01/2019 ~ 05/2019

used Angular.js front-end framework, flask back-end framework and MongoDB database to develop dynamic and interactive website that ensured high traffic, page views and user experience.

user can get the predicted result of stock in the short and long term according to the indicators and their choices.

Machine learning methods, such as Bayesian Curve Fitting, Artificial Neural Network and Support Vector Machine, are applied to the prediction.

Credit scoring system based on logistics regression 01/2016 ~ 05/2016

Data preprocessing include data cleaning, missing value and outlier processing.

Statistical method is used to explore the data distribution and select variable.

Model development includes variable segmentation, variable (WOE)weight of evidence transformation and logistic regression estimation.

Model evaluation is to evaluate the distinguishing ability, predictive ability and stability of the model.

Built a credit scoring system through using logistics regression to fit the data and then got the credit score based on coefficients of logistic regression and WOE, in the end, evaluated the result through ROC curve. Competition

National Business Simulation Competition 05/2014 ~ 05/2015

Applied interdisciplinary knowledge, developed quantitative strategies during the competition against the students from universities around the nation and get 1st prize.

Solved some problems in the fruit processing plant through using the Branch and Bound Algorithm to optimize manufacturing processes and increase the production capacity by 20%. Challenge Cup National Undergraduate Business Plan 04/2013 ~ 12/2013

multivariate statistical analysis and time series method to analyze the historical data to get the best strategy in market.


Outstanding Graduate Scholarship (1 %) 06/2016

First Prize in the National Business Simulation Competition 05/2015

Third Prize in the Challenge Cup National Undergraduate Business Plan 12/2013

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