Social Media Data

Miaochao Wang

*** ******** ***** ****, ***** City, NJ 07087

201-***-****, *******@*******.***

SKILLS: Programming Languages: Python, R, C

RDBMS: MySQL, MS SQL Server, PostgreSQL

Analytical Tools: Tableau, Advanced Microsoft Excel, Microsoft Access, STATA, SPSS, SAS JMP, Alteryx

Machine Learning: Logistic Regression, Random Forest, K-Means Big Data Tools: Hadoop, Spark, MapReduce

Experimental Design: A/B testing, Multivariate testing EDUCATION: Stevens Institute of Technology, Hoboken, NJ Expected May 2018 Master of Science in Business Intelligence & Analysis GPA: 3.94/4.0 Course: Statistical Learning & Analysis, Multivariate Data Analysis, Optimization and Process Analytics, Data Mining, Risk Management, Data Warehousing

Southeast University, Nanjing, China Aug 2012 - Jun 2016 Bachelor of Economics GPA: 3.31/4.0

EXPERIENCE: Pfizer, Peapack, New Jersey, United States May 2017 - Dec 2017 Data Scientist Intern

• Scheduled weekly report and updated subscription with the help of SQL Server Integration Service and SQL Server Report Service to accelerate the workflow within 1 hour

• Cleaned data including data format design, data interpretation and data integration and built the data preparation pipeline

• Designed Medical Industry Data Reports and analyzed trends using Tableau with senior management teams for different vendors to assess and reduce cost for 3%

• Operated exploratory analysis on different vendor records, conducted statistical analysis including Confidence Interval and hypothesis testing using R and visualized the results with various R packages

(Shiny, ggplot, knitr, etc.) to automate analytics life cycle

• Engaged in Cost of Quality Project, building models and Control Chart to predict and increase the benchmark performance by 10%

Stevens Institute of Technology, Hoboken, New Jersey, United States Sep 2017 - Dec 2017 Research Assistant

• Carried out exploratory data analysis, generated and tested working hypotheses to help L’Oréal HR Department uncover 100,000 data points in 20 years’ records by Python

• Performed Data Wrangling operations and integrated feature engineering to identify, measure and recommend improvement strategies to potentially increase 5% of KPI evaluation matrix performance

• Built several Machine Learning Models to predict staff turnover rate by using ANN, Random Forest, Logistics Regression and Gradient Boosting and achieved 93% accuracy based on Cross Validation Schneider Electric, Beijing, China Aug 2015 – Dec 2015 Marketing Assistant Intern

• Collected and performed analysis on market data from vendors to maintain company’s database

• Supported the upgrade of company website and social media accounts

• Collaborated with several departments to publicized the activities during conferences

• Participated in contacting suppliers, confirming price, ordering, and payment process with managers PROJECTS: Kaggle Competition: Two Sigma Rental Listing Classification Analysis Feb 2017 - Apr 2017 Bronze medal, 127th place out of 2488, Top 5%

• Operated explanatory analysis on apartment rental listings using R and Python

• Engineered over 500 features including sparse data based on 6GB data such as text description, photos, number of bedrooms, price, etc.

• Applied KNN, Naïve Bayes, CART, Logistic Regression and Support Vector Machine Algorithms to increase company’s baseline listing interest level performance by over 50% AWARDS: Kaggle Expert Nov 2017

• Completed a significant body of work on Kaggle in one or more categories of expertise

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