JINGYAN (JANE) CHEN

adg5nx@r.postjobfree.com 347-***-**** https://www.linkedin.com/in/jingyanchen398/ SKILLS

Python (Pandas,Numpy,Plotly,Seaborn, Selenium) Tableau SQL ETL AWS RDS, EC2, S3 R SPSS Google Analytics Salesforce EDUCATION

Fordham University, Gabelli School of Business, Master of Science in Business Analytics, GPA:3.9/4.0 08/2018-02/2020 Related Coursework: Database management, Web Analytics, Text Analytics, Data Mining for Business Nanjing Normal University, Bachelor of Economics and Management, Accounting, GPA:3.5/4.0 08/2014-06/2018 Related Coursework: Applied Statistics, Financial Analysis, Security Analysis and Investment WORK EXPERIENCE

Enablement Data, Data Analyst, NY 09/2019-Present

• RFM customer segmentation model: built membership strategy by RFM model through Python and Tableau, stimulated sales team and brought in 10% increase of revenue.

• SMS Campaign data analysis: conducted EDA analysis and deployed a report that provided insights of geographic and industry preference occurred when generating leads via SMS campaign. Designed a A/B testing on new version of landing page, calculated sample size and increased 3% of conversion rate.

• Sales funnel analysis: developed a funnel analysis by utilizing data from CRM system, computed conversion rate in each part of funnel, and visualized lost purchase rate by frequency. Presented result to management team and helped better understand health of business.

• Customer cohort analysis: created cohort analysis on both customer retention rate and revenue retention rate, segment analysis by different product lines and customer groups, found most valuable products and clients.

• Customer lifetime value analysis: designed a dashboard showing up CLV within 3 years, segment analysis by different products and client groups. Analysed expansion and cross sell revenue, found churn rate pattern, developed a better CLV formular for estimation.

TUNIU Financial Information Services Co., Ltd, Intern of Credit Business Department 05/2018-08/2018

• Income statement analysis: measured potential clients’ business performance by different metrics like profit margins, ROE.

• Structural credit risk analysis: Aggregated more than 500,000 transactional data, integrated customer records with Pivot table and VLOOKUP in Excel. Conducted a structural credit risk analysis, measured the value of equity and debt, measured risk of investment, generated report and presented to clients. PROJECT EXPERIENCE

Web Traffic Analysis

• Analysed the performance of web traffic from different dimensions, selected conversion rate, click through rate and bounce rate as metrics, segment analysis by different traffic sources and marketing channels.

• Utilized the quality of leads that generated through different channels and different time to measure the traffic performance, found both internal and external reasons that cause the big difference in first quarter this year.

• Through the analysis, figured out the lead generated from organic search and Facebook ads were most valuable leads. Text Analytics: studying Alexander Wang’s Effect on Fashion Brand that collaborates with Adidas, H&M and Uniqlo

• Scarped 11,805 comments from related articles in fashion magazines, Twitter, and Instagram through Python, analyzed texts from three collaborations with SPSS to develop conceptual model.

• Conducted sentiment analysis, understood the attitude of the consumer towards the collaboration, their willingness to buy the products of the collaboration, analyzed whether the collaboration has a positive effect on the companies’ sales and found out most related topics about collaborations.

• Most of customers have a positive attitude towards all three collaborations, which can be correlated in the people’s willingness to buy, shown in the increase in sales during the collaboration periods. Big Data Analytics: Kaggle Competition – Expedia Hotel Recommendation

• Built a recommendation system with ALS model in Pyspark, selected 23 features capturing the logs of customer behaviors, found out the most popular clusters of hotels and which main factors could influence whether customers are booking or not.

• Conducted EDA analysis and visualized over 30 million rows of data by Python, created a decision tree and logistic regression models by SPSS, estimated the booking status of customers and several significant factors that impact the result.

• Developed recommendation system for each user. Based on destination, assign scores to each hotel cluster, recommended ten different hotel clusters for each destination and each user. Database management: creating database instance on AWS RDS service, data ETL pipelines

• Designed ER-diagram, created DDL, setting up a relational database instance on AWS RDS service. Assigned different permissions and authorities to users and manage database better.

• Created data pipelines by using Python, transformed, retrieved, and loaded data from database. Wrote complex SQL queries to update and lookup database.