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Data Analysis, Data Science

Madison, Wisconsin, United States
January 20, 2018

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Huanwen (Ellie) Wu

**** ********* *** ***, ** ***05 608-***-****


Seeking a position in data analysis or data science, utilizing my experience and skills in statistics and machine learning EDUCATION:

University of Wisconsin-Madison

Department of Statistics, Master of Statistics (GPA: 3.7) Sept. 2015-May. 2017 East China Normal University

School of Finance and Statistics, Bachelor of Statistics (GPA: 3.4) Sept. 2012-June. 2016 COMPUTER SKILLS & CORE COURSES:

R, Python, SQL, Shell, Excel, SAS, C++

Machine Learning, Data Science in R, Decision Tree, Experimental Design, Probability Theory, Statistical Inference, Time Series, Financial Statistics, Statistical Method


Data Analysis of Car Crash Test by Multiple Methods Jan. 2017-May. 2017

• Investigated abnormal values, performed transformation of special variables and imputed missing values for the database (R)

• Built decision trees including random forest, rpart, ctree, cforest, as well as logistic regression model and lasso regression model to estimate the seriousness of car crashes (R/Python)

• Compared different methods in running time and the performance of model prediction Segmenting Trump’s Twitter Followers during 2016 Election May. 2017-Aug. 2017

• Assisted with a research about segmenting Trump’s followers, participating in data preparation, clustering and visualization

• Conducted data acquisition through Twitter API and web scraping, developed automatic scripts for fetching information of Trump’s followers (R/Python)

• Built followers segmentation models using clustering method and performed data visualization by ggplot2 to explain the roles each segment of Trump’s followers played during the election (R)

• Under the hypothesis that bots have fewer followers thus lower PageRank score, produced plots to identify possible web robots in

“supporters” segment (R)

Text Analysis about Customer Reviews of Airbnb Listings: Evidence from NYC Sept. 2016-Dec. 2016

• Crawled textual data from website. Merged tables to acquire reviews of 70,000 unique customer ids (R/Shell)

• Conducted text mining, eliminated stop words, counted word frequencies and transferred the most frequent words into vectors by using one hot encoding (R)

• Clustered customers by K-means algorithm based on their reviews and performed further analysis to figure out the characteristics of the clusters (R)

Implementation of Discovering Latent Network Structure in Point Process Data Jan. 2017-Apr. 2017

• Built a Hawkes network model based on the Hawkes process to find the connections among processes (Python)

• Applied annealing algorithm to Gibbs sampling to estimate the parameters with maximum posterior probability

• Tried different functions to describe the impulse response of influence of one event on another process INTERNSHIP EXPERIENCES:

Data Analyst Internship at Alibaba Group (Ant Financial), China July 2014-Aug. 2014

• Extracted, transformed and loaded transaction data with billions of records to help with the team’s core project of producing a big data based financial index named CSI Taojin Big Data 100 index (SQL)

• Prepared data for industries with transaction records, price levels and the “supply-demand situation” to weight industries and calculate individual stock positions based on weightings (SQL/R)

• Performed category mapping for industries between Taobao transaction dataset and Tianhong Funds dataset to unify the structures of category levels and accelerate the processing of querying for a money market fund “Yu’e Bao” (SQL/Excel) Summer Internship at ZheShang Securities Co. Ltd. China July 2016-Aug. 2016

• Made data research on company-based data, analyzed the financial statements of customer companies

• Conducted due diligence, made enterprise investigation, travelled on business and wrote reports AWARDS & CERTIFICATIONS:

Financial Risk Management (FRM) Certification, US Jan. 2018 SAS Base Programming Certificate, US Sept. 2017

Second Prize of Mathematical Contest in Modeling (MCM), US Feb. 2015

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