Data Analyst Project

YIJIE SUN

917-***-**** • *****.*****@*****.***

*** ****** ******, *** ****, Jersey City, NJ 07302

EDUCATION

Fordham University, Gabelli School of Business New York, NY MS in Information Systems GPA: 3.79/4.0 Aug 2016 – Dec 2017

• Relevant Coursework: Data Mining Database Management Programing with Python R Statistical Programming Web Application Development Big Data Analytics

Jinling Institute of Technology Nanjing, China

BA in Financial Management Sep 2011 - Jun 2015

• President of Student Union

• Excellent Student Cadre

• Volunteer supervisor of Youth Olympic Games

PROFESSIONAL EXPERIENCES

Fundways New York, NY

Digital Data Analyst Feb – Jun 2018

• Created ads on Google Adwords and tracked ads’ performance

• Worked with website developers and UI designers to change the layout and content of the new-built website

• Tested website functions and enhanced SEO

• Analyzed on site activities and monitored KPIs using Google Analytics

• Adjusted advertising strategy according to observed user behavior Eastone Capital New York, NY

Data Analyst Intern Nov 2017 – Feb 2018

• Reformatted and cleaned client information for data analysis

• Inserted and retrieved records into database using SQL

• Used Tableau and R to interpret and present results to director and marketing team RELEVANT PROJECT

Barneys New York Sales Improvement New York, NY

Web Analytics Project Aug – Dec 2017

• Applied Python to crawl 15,000 twitters of Barneys, Bergdorf and Saks

• Conducted image analysis using Google Cloud Vision API to obtain picture labels from over 4,000 images and to identify the most popular fashion items mentioned by Barneys, Bergdorf and Saks

• Generated word count and analyzed the similarities and differences among three department stores

• Classified 4 groups of brands to which Barney's should pay more attention Kobe Shot Analysis New York, NY

R Statistics Project Aug – Dec 2017

• Manipulated data to required format, removed unrelated features and split data into training and testing set

• Used ggplot to find obvious correlations between features and target

• Selected features using lasso regression to build linear regression model

• Predicted new data with glm and compared predicted and actual values with confusion matrix Yelp Online Marketing Optimization New York, NY

Big Data Project May – July 2017

• Utilized Python to crawl over 20,000 businesses and reviews data in 20 big cities from Yelp API

• Analyzed Yelp reviews and distinguished positive and negative reviews using sentiment analysis

• Applied Microsoft Azure API to analyze to generate 5 features with the highest confidence for each images and visualized results using Tableau

SKILLS

Data Analysis: SPSS Modeler, Google Analytics, Oracle Database, MySQL, Google Cloud Vision API, Microsoft Azure API, Tableau, Excel (VLOOKUP, PivotTable, What-if Analysis, Scenario Analysis) Programming: R (ggplot2, dplyr, linear regression), Python (numpy, matplotlab, pandas), SQL, PHP (some knowledge) Big Data: Google Big Query, MongoDB (some experience), Hadoop (some experience) Other: Google AdWords, MS Project, Final Cut Pro, Word PowerPoint

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