Sales Customer

JING ZHANG

858-***-**** ****.*****@****.****.*** www.linkedin.com/in/jingzhang14

Education

University of California, San Diego

Master of Science in Business Analytics, Rady School of Management, Dec. 2017

• GPA: 3.65/4.0

• Rady Fellowship, 2016

• Relevant Courses: Collecting and Analyzing Large Data, Experiments in Firms, Business Intelligence Systems University of International Business and Economics Bachelor of Science in Finance, Beijing, China, Jun. 2016

• GPA: 3.60/4.0

• Third Class Academic Scholarship, 2015 (Awarded for top 20 GPA) Experience

Data Analyst Summer Intern, ASML Cymer, San Diego Jun.2017 – Sep.2017

• Automated weekly EUV dose error analysis report plotting making process with R and MATLAB from 1 hour to 5 min

• Created a data analysis GUI in R for engineers to apply customized functions and machine learning algorithms to understand correlations of KPIs of EUV machines

Capstone Project in Pricing, Hewlett-Packard, San Diego Apr.2017 – Aug.2017

• Led 4-person team on data cleaning, modeling and presentations to HP PMs and leadership

• Built various models to evaluate price elasticity and internal cannibalization effect of each product

• Created a decision-making app to visualize sales history and provide optimized promotion amount for each product Research Assistant in Text Mining, UCSD, San Diego Jan.2017 – Apr.2017

• Text mining of 1.3 million UGC descriptions of 4700 advertisements with R

• Performed LDA topics modeling to cluster customer feedback and preference

• Analyzed six sentiments of each ad (joy, surprise, sadness, disgust etc.,) to recognize customer reactions

• Used TF-ITF to identify key features in each ad, and predict brand and category of each ad Customer Analytics Project, UCSD, San Diego Apr. 2017– Jun. 2017

• Adopted multiple machine learning algorithms (RFM/ Naïve Bayes/ Logistic Regression/ Neural Network) to analyze and predict customer purchase behaviors under E-commerce environment

• Designed randomized experiments to collect customer information

• Predicted customer churn, identified the main drive of churn and defined preventive measures Retail Business Analytics Intern, Nielsen, Beijing Apr.2016 – Jun.2016

• Tracked and analyzed clients’ daily and monthly retailing data in food and commodity categories to identify market trends and provide stock and marketing recommendations

• Identified pattern in purchasing behaviors by conducting preliminary analysis and in-store customer investigation on holiday sales performance for Carrefour and local Chinese supermarkets to help them prepare for next event sales Specialized Skills

• Coding: R(advanced), Python(intermediate), SQL(intermediate), Tableau(intermediate), Radiant(advanced)

• Languages: Mandarin(native), English(advanced)

• Algorithm: Decision Tree, Naïve Bayes, Neural Network, Logistic Regression, Latent Dirichlet Allocation Professional Affiliations & Interests

• Rady Data Analytics Club (Member)

• Rady Technology Club (Member)

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