Data Analyst Sales

Yudong Shi

972-***-**** ***.*******@*******.*** www.linkedin.com/in/charlie-shi

EDUCATION

Master of Science, Management Science (Business Analytics Track), The University of Texas at Dallas, August 2017 – May 2019 Bachelor of Arts, English, Dalian University of Foreign Languages, August 2009 – May 2013 SKILLS

Technical: Excel (Pivot Table, VLOOKUP, Macros), Python (NumPy, Pandas, scikit-learn, TensorFlow), R, SAS, SQL, Access, SAP BusinessObject, ETL, Tableau, Power BI, Google Analytics, Google AdWords, Adobe Analytics, Facebook Ads Data Analytics: Statistical Analysis, Data Cleaning and Manipulation, Modeling, Machine Learning, Visualization, and Reporting Sales Analytics: Planning and Forecasting, Market Analysis, Campaign Mgt, Performance Metrics, Salesforce, CRM PROJECTS

August 2017 – May 2019

Predict Australia Rain Precipitation Using Python

- Cleaned and manipulated 142k unstructured data. Trained regression, classification, and machine learning algorithms using KNN, Naive Bayes, Decision Tree, and Random Forest to predict precipitation probability. Use the ROC Curve and AUC Score to select the best model. Applied Neural Network to improve model chosen accuracy to reach 84%. Product and Market Analysis Using Excel and Tableau

- Created Tableau dashboards to understand consumer characteristics in driving the business, built logistic regression models in Excel and Python to conduct causal analysis and validate findings, summarized insights, and proposed recommendations on future business development strategy and sales approach.

Tattoo Studio Market Campaign Using Google Analytics, AdWords and Facebook Ads

- Generated 13.4k online impressions from Google and Facebook Ad platforms in three weeks to increase studio brand awareness in the targeted market. Helped client to identify new selling point ‘Oriental Design’ from visitor behavior. Use SEO incorporated geo- targeting and other functions to provide campaign insights. Research on Relationship between Unemployment Rate and Homicide Rate Using MySQL, SAS and STATA

- Used SQL queries to exact a three-year dataset and imported it into SAS and STATA. Built statistical models like time series regression and fixed-effects model on cross-sectional data and panel data to find and validate the correlation between unemployment and homicide. BUSINESS EXPERIENCES

TESLA, Product Specialist, Beijing CHINA, March 2017 – July 2017 Educate a B2C market with a stereotype, raised consumer interest, addressed their concerns, and generated 15 to 25 quality leads daily. Facilitated purchase by invite 5 to 10 groups every week for a test drive and to stimulate desire, with a customized financial solution. Increased leads to sales conversion ratio by managing the Salesforce pipeline, which generated $90k to $0.37m in revenue every month. Delivered business intelligence analysis on the product, consumer, and competitors, to improve sales procedures and practice. GRAND HYATT, Sales Manager, Beijing CHINA, May 2013 – July 2016 Excelled in a saturated B2B market and increased revenue for 5-8% in three consecutive years. Developed five acquisition accounts, which later contributed a 20-30% increase in the annual number of room nights, a KPI. Conducted market analysis to find new growth potential from accounts in education industries, which later contributed $87k in revenue in the first year. Designed customized marketing campaigns and deals to counterstrike direct and indirect competitors. Evaluated performance and develop strategies by utilizing Excel reports and dashboards to understand drivers and outliers, connection and patterns. Address the weakness, enhance the efficiency of the workflows, and ensure actions are leading to gain market share. Managed customer relations (CRM) by maintaining strong bonds over 400 account decision-makers and influencers. Interfaced with multiple internal and external departments to create seamless guest experiences, which helped overcome buyer’s remorse. WALT DISNEY WORLD, Cast Member, Orlando FL, August 2011 – February 2012 Created Disney Magical Moments for guests of all ages when they watch live performances or participate in park attractions. Promoted Disney merchandise and anticipated guest demands, in return, received a high guest satisfaction rate.