JINGJING CHEN 1230 Amsterdam Ave, Apt 533, New York, NY, 10027 Phone: 347-399-7672 Email: jc4094@columbia.edu

EDUCATION Teachers College, Columbia University M.A. in Economics and Education, GPA: 4.02/4.00 May 2015 Courses: Data Mining, Multilevel Data Analysis, Statistical Computing with SAS, Data Analysis and Graphics in R Central University of Finance and Economics, Beijing B.A. in Economics, GPA: 92/100 June 2013 Courses: Applied Statistical Computation, Econometrics, Finance, Asset Pricing, Financial Report & Analysis

Massive Open Online Course (Mooc) 2014 R Programming, Developing Data Products, Interactive Programming in Python, Practical Machine Learning

SUMMARY OF SKILLS Data packages: R, SAS, Stata, SPSS, Excel(VBA, Pivot Table), Bloomberg Terminal; learning Python, SQL, Hadoop Certifications: SAS Certified Base Programmer (preparing for SAS Advanced); CFA Level I Language: Chinese (Mandarin): native proficiency; English: professional proficiency

INTERSHIP Business Intelligence Analyst, 17Zuoye, Beijing Jan. - Mar. 2015 Obtained, cleaned, processed and stored the data using Python and SQL for data science department Defined key business concepts, i.e. active user, potential customer, for business development department Visualized data to inform principals how teachers’ time is saved and students’ academic performance improved Analyzed characteristics of fee-paying users so that marketing dept. could better focus on potential customers Data Analyst, Technical Consulting & Research, New York City Apr. – Dec. 2014 Visualized educational survey data using plotrix, likert, dplyr, ggplot2, knitr, shiny packages in R Conducted cost-benefit analysis and helped customer to allocate limited resources Published a paper “How Big Data Can Drive Excellence in Education” and gave a presentation on 2014 CEWIT Business Analyst, IBD, Bank of China International, Beijing Mar. –Jun. 2013 Underwrote a publishing company, responsible for modifying prospectus, following feedbacks of SEC and

accounting verification and also in charge of pitch books and TMT weekly report Participated in a M&A project of a state-owned enterprises, responsible for industry and financial analysis

PROJECT Text Mining of Capital Facility Finance Bond Elections --- text mining, LDA Nov. – Feb. 2015 Applied Latent Dirichlet Analysis and Correlated Topic Model in R to analyze full text of bond election proposals Identified 9 different latent topics, including requests to buy new buildings, renovations, and athletic facilities Examined the independent effect of the bond topics on the probability of passing the bond and voter turnout Published a paper “Ask and Ye Shall Receive? Automated Text Mining of Michigan Capital Facility Finance Bond

Election Proposals to Identify which Topics are Associated with Bond Passage and Voter Turnout ’’ Text Classification of the Federalist Paper --- data mining, Classification Nov. – Dec. 2014 Implemented an authorship attribution algorithm for the Federalist dataset using a Naïve Bayes classifier in R Built the Federalist Papers’ dictionary to extract and summarize the feature of each paper Implemented & compared other classification methods, including decision tree, logistic regression (Ridge and

Lasso), cross-validation and SVM ( with Gaussian kernel and linear kernel), with Naïve Bayes classifier

Face Recognition of Yale Face Database B --- data mining, PCA& kNN Sep. – Oct. 2014 Wrote loops to automatically load the faces data into R, reconstruct and combine the data Examined all of the steps to reduce dimension of cropped face images by PCA Divided the data into training and testing sets, did PCA on training set and used kNN classification to identify

the subject for each testing observation