OBJECTIVE: To obtain an internship or full-time job in the field of Business Analytics or Data Analytics.
Highly resourceful, process-focused and detail-oriented person with noteworthy internship and project (equivalent 2 years) experience in the business fields (Insurance and Bank) while maintaining a strong sense of responsibility, time, and team spirit. A quick learner who can adapt to a new environment.
Talented in building strong partnerships at all levels while maintaining excellent written and verbal communications - Bilingual proficiency in Mandarin (Native) and English (Fluent).
Technical Skills: Python, R, SQL, Tableau, AWS, SAS, Excel Pivot Table, Google Analytics, Hadoop, Spark, AMPL, etc.
Master of Science (M.S.) The GEORGE WASHINGTON UNIVERSITY August 2017 – December 2018
Business Analytics GPA 3.6 School of Business Washington, DC
Coursework: Programming for Analytics, Decision and Risk Analytics, Digital/Web & Social Analytics, Data Management for Analytics, Time Series Forecasting, Data Mining, Big Data, Optimization.
Certification: Google Analytics Individual Qualification, Business Management Skill Development Certification.
Bachelor of Science (B.S.) PURDUE UNIVERSITY December 2013
Management (HR) GPA 3.7 Krannert School of Business West Lafayette, IN
Dean’s list (7/7 Semesters)
Study Abroad, School of CIMBA in Italy
BUSINESS ANALYTICS RELEVANT PROJECTS
TEAM PROJECT #1: Deloitte Practicum Project London Tourism Analytics August 2018 – December 2018
OBJECTIVE: The City of London’s local ministry has requested analytics advisory services from Travel-The-World (TTW) Analytics Management consulting working in close consort with the London Tourism Bureau (International Tourism Data, 2002-2017) to construct foundational predictive capabilities, centered on monitoring city’s tourism growth relative to distinct EU member nations and the overall global community.
As a team together, we first make our Project Plan & Timeline. We plan to meet our mentors and professor bi-weekly to discuss what we need to do in the next two weeks.
Data Visualization & Data Exploration: Our first stage is to explore our data and visualize the data (Python & Tableau) so that we might have some idea about the data and can find some interesting topics to work on.
TEAM PROJECT #2: Kaggle Open Data Competition House Price in Iowa January 2018 – May 2018
OBJECTIVE: With 79 explanatory variables and 1500 observations describing almost every aspect of residential homes in Ames, Iowa, this project is aimed to predict the final price of each home and find out which variables have the largest influence on the final price of each home. Developed several deep learning, neural network, decision tree (random forest) and regression models with different variables encoding technical to predict the housing price in Iowa.
Data Exploration: Use the log transformation to get rid of the right-skewed problem of the target variable, Sale Price. By looking at the correlation plot, 9 variables are highly correlated with the target variable. Drop some outliers, split 30% of the train data into validation data in order to avoid leakage.
Data Preparation: Drop uncorrelated variables. Impute missing value based on variables’ types (categorical or numeric). Add useful variables, change some numerical variables that should be categorical, and drop several highly correlated variables to solve the multicollinearity issue. Apply ordinal encoding, label encoding, and one-hot encoding based on the meaning of each variable.
Models Building: Regression, GBM, Neural Network, and Feature Extraction (Lasso Cross-validation).
Evaluation and Selection: Identify the most promising model based on the validation data set and the RMSE score. The best model is the average model by combining the top 3 models.
Final Ranking: The best model achieved the top 6% ranking on Kaggle with the RMSE score is 0.11540.
TEAM PROJECT #3: YELP PROJECT Travel Brochure for Couples in Las Vegas August 2017 – December 2017
OBJECTIVE: Find an interesting data set from yelp to develop a seamless story by applying Python, MySQL, ggplot, and matplotlib packages. Provide 5 minutes of YouTube video.
Topic and Story Line: Design A Travel Brochure About the Romance Trips for Couples in Las Vegas. A travel agency located in LV asked a group of BA students to help them design a travel brochure for couples to travel to LV.
Teamwork and Leadership: Filter closed business out and divide the open business into 3 categories: Hotels, Restaurants, Activities and Entertainment. Search keywords related to “romance” and set 3 price ranges.
Result: Based on rating and review counts, provides the top 3 choices on Hotels, Restaurants, Pubs, and Attractions, then making a Google map to show the directions. Customers can finalize their trip route (customized service).
INDIVIDUAL PROJECT #4: RSHINY PROJECT Traffic Accidents in Maryland August 2017 – December 2017
OBJECTIVE: Find a data set in certain websites, identify several interesting questions and build an RShiny application. use R and leaflet package to help respond to those questions. Provide a 3 minutes YouTube video.
Topic and Questions: Traffic accidents in Maryland from 2012 to 2017. Which street/month/weekday/hour have the largest number of accidents in those 6 years.
Result: After dividing the date and time into new columns (Year, Month, Day, Weekday and Hour) and applying the interactive RShiny application to visualize the data set, I found that 2015, July, Friday, Sixth and Seventh of each month, and 5 P.M. have the largest number of total accidents.
Perform as data & operation assistant, HR Intern, and Project Intern at China Taiping (One of the four State-Owned financial and insurance Company in China, headquartered in Hong Kong. The first transnational financial insurance company in China.) Strong project related experience and ability to handle multiple tasks simultaneously. Learned about the company’s structure and culture.
Data and Operation Assistant Analysts TAIPING LIFE INSURANCE CO., LTD, Harbin, Heilongjiang, China July 2017 – August 2017
Conducted considerable data collection about office rental and reasonable use in order to better serve the frontline, meet the development needs, so as to achieve the goal of reasonable resource matching and cost optimization.
Analyzed the current workplace area/status, the reasonable degree of workplace decoration, employees’ actual attendance and performance, employee’s difficulty with retention, area waste due to dismission, and the company’s revenue.
Established rules that the company must achieve a stable manpower scale, which must last longer than 6 months and the attendance rate no less than 50% so that the company can increase office space.
Determined that the company needed to downsize the rental and use of office space instead of upgrading the space to maximize efficiency, reasonability, and practicality.
Human Resource Department TAIPING PENSION CO., LTD, Harbin, Heilongjiang, China August 2014 – June 2015
Mediated conflicts between employees, planned and coordinated workers to best use employee’ talents, engaged in training and development, managed employees’ files and contracts (Labor Relations Management).
Analyzed personnel expense budget, confirmed payroll and welfare, handled social security and personal taxes, processed relevant adjustments and reimbursements with accuracy, issued employee income certification (Salary Management).
Managed employees’ attendance while tracking employee performance, provided early warning and implemented assessment results, calculated and managed bonuses (Performance Management).
Business Associate Rotation Program TAIPING LIFE INSURANCE CO., LTD, Harbin, Heilongjiang, China June 2013 – August 2013
Cooperated with all the teams and departments to schedule meetings, monitored projects process, and reduced mistakes.
Managed and developed biweekly reports for organizational supervisors and analyzed retail sales data; provided a monthly presentation to target departments and updated the business plans and goals, increased sales by 2% monthly.
Perform as data and customer manager assistant at Industrial Bank (One of the first batches of the joint-stock commercial bank approved by the State Council and the People’s Bank of China.) Strong experience to lend loan to potential enterprises by working with managers through the pre-loan background check, loan design and promotion, and post-loan periodical inspection.
Data & Customer Manager Assistant INDUSTRIAL BANK CO., LTD, Harbin, Heilongjiang, China May 2017 – June 2017
Identified target enterprise, learned the overall situation of the enterprise by communicating with its senior executives during the pre-loan process, such as get to know the establishment of the enterprise background, shareholders’ background, main business and overall industry situation, proportion and market position in the industry, operation condition, etc.
Promoted and designed loan package to the potential enterprise in the loan process after rigorous pre-loan inspection.
Analyzed the risk of investment packages and individual loans in the post-loan process by paying attention to all aspects of the enterprise to prevent the deterioration of operating or financial conditions from affecting repayment ability.
ADDITIONAL PARTTIME WORK EXPERIENCE
Retail Customer Service Manager SANA ZOAN COFFEE HOUSE, Harbin, Heilongjiang, China July 2015 – December 2015
Revised and redesigned menu by proactively gathering guests’ feedback, increased sales by nearly 2% quarterly.
Developed surveys with the customer service team and interviewed customers, reduced complaints by 5% quarterly.
Teacher’s Assistant PURDUE UNIVERSITY, West Lafayette, IN January 2013 – May 2013
Organized and managed study group sessions with a total of 150 students.
Collaborated with the professor weekly to successfully answer students’ questions and concerns.
Community & Leadership: Nursing Home of RunFu; Akron Food Bank; Purdue Pre-Law Society; Society for Human Resources Management; Purdue Passport Group.
Additional Study & Certification: Studied Law at UNIVERSITY OF AKRON in Ohio for one year. National LexisNexis Certification.