Data Analyst Python

Binbin Weng

***********@*******.*** 214-***-**** RELOCATABLE SAS & Google Analytics Certified

•Solid background in reporting, data wrangling, predictive analytics, and data modeling with Python, SQL, SAS.

•5-year experience with building models on large-scale datasets with advanced statistical modeling, deep learning, and machine learning methods.

•Creative, effective, adaptive, organized in different working environments. EDUCATION

The University of Texas at Dallas December 2017

M.S. in Business Analytics (STEM) GPA: 3.83

SKILLS

•Languages: Python, SQL, VBA, HTML

•Databases: MS SQL server, MySQL, Access

•Analytical and Data Visualization Tools: SAS, R, Tableau, Excel, MATLAB

•ERP System: SAP

WORKING EXPERIENCE

Javelin Agency, Irving, TX June 2019 - Present

Statistical Analyst

•Perform marketing mix modeling to analyze the impact of over 1 billion dollars per year total value marketing mix ele- ments on sales.

•Develop and maintain systems using VBA to automate the weekly model scoring process that tracks marketing media ROI and saves over 1200 hours per year.

•Batch collect data from databases in Unix environment, dig in data with MS SQL Server, build classification models such as XGBoost, Neural Network, Logistic Regression, SVM, Random Forests, and segmentation models such as K-Means, KNN, with SAS and Python, and visualize results with Tableau, to provide clients more insights for their strategies.

•Automate the 2-sample t-tests in the multi-dimension monthly reputation score report with MS SQL Server.

•Conduct research to perform Bayesian estimation of exogenous variable coefficients in time series model. Samsung Electronics America, Richardson, TX December 2017 - June 2019 Supply Chain Analyst

•Reduced team’s working time 25% while increasing accuracy 37% by creating macros in SAP to optimize the order man- agement process; automated tasks such as changing order information, dropping orders, and creating orders.

•Pulled data from database using SQL to create weekly OTD/LD reports to forecast potential shipping and product quality issues, and avoided roughly $250K of late delivery fees in 2018

•Overhauled order fulfillment team’s handling of shipping information by building a database with MS SQL Server to con- solidate all pertinent information previously stored in various locations.

•Streamlined data retrieval process by creating VBA macros to extract important and needed data from different sources such as internal systems, txt. files, PDF files, Salesforce, and e-mails. Zuri Furniture, Dallas, TX January 2017 – December 2017 Data Analyst Intern

•Impacted sales growth through building customer classification models based on 30K current customers’ information us- ing SAS, and A/B tests on different versions of promotion emails.

•Organized inventory by extracting over 10,000 SKUs using SQL, transforming and loading data into new ERP system.

•Delivered results for enhancement of product webpage layout by using market basket analysis with SAS to analyze the relationships between products for an improved online consumer experience.

•Gathered and mapped data with SQL to conduct ad-hoc analysis on warehouse KPI, shipping cost and inventory fore- casting reports; extracted data into readable graphs for presentations with Tableau.

•Analyzed shipping costs and determined shipping priorities and methods, saving $100K shipping cost in one season. PROJECT EXPERIENCE

Aerial Cactus Identification (Python, accuracy rate 99.98%)

•Built deep learning models to determine whether an image of vegetation contains a columnar cactus, with Convolutional layers, Pooling layers, Flatten Layers, Fully Connected layers using TensorFlow. NLP on Amazon Reviews (Python, accuracy rate 85%)

•Preprocessed Amazon review texts by regular expression, lemmatization, tokenization, stemming, td-idf score.

•Developed sentiment analysis models to predict if a customer likes the product or not, using Naïve Bayes, SVM and Random Forest, and deep learning model (LSTM) with TensorFlow.

Contact this candidate