Continuous Improvement Engineer

San Francisco, CA PUWEN NING 812-***-****

*********@*****.*** linkedin.com/in/puwenning

EDUCATION

Indiana University Bloomington 08.2014 – 05.2016

M.S. in Statistical Science (GPA: 3.8/4.0)

Coursework: Machine Learning, Statistical Inference, Design of Experiments, Exploratory Data Analysis Shanghai Jiao Tong University 09.2008 – 02.2011

M.S. in Material Science and Engineering (GPA: 3.6/4.0) Soochow University 09.2004 – 07.2008

B.S. in Material Science and Engineering (GPA: 3.7/4.0, 4 out of 55) PROFESSIONAL EXPERIENCE

Indiana Statistics Consulting Center 08.2015 – 05.2016 Consulting Intern

Assisted clients with statistical consulting. Major clients are from various domains such as Public Health, Psychology, Education, Business, Biology and other fields

Performed statistical analyses using t-test, Chi-square test, ANOVA, Power Analysis. Developed models such as Logistic Regression, Generalized Linear Model, Support Vector Machine with R, SPSS and Excel

Completed one project per week on average. Accomplished 20 projects totally within two semesters Indiana University Bloomington 01.2016 – 05.2016

Teaching Assistant

Assisted in teaching course STAT-S303 Statistics for Life Sciences with Professor David King Semiconductor Manufacturing International Corporation (NYSE: SMI) 02.2011 – 08.2014 Yield Analysis Engineer

Improved wafers yield on China’s most advanced semiconductor foundry process. Chip designs are mainly from leading design companies such as Qualcomm, Broadcom and Texas Instruments

Analyzed wafer map patterns and yield trends using Exploratory Data Analysis, ANOVA, Linear Regression with R, SQL, Excel and JMP. Identified root causes of 3 high impact zero yield cases

Designed experiment to solve inadequate capacity issue for various products such as iPhone 5s Bluetooth, Qualcomm Power Management IC device. Optimized process recipe and product performance

Generated $1,500,000/year cost saving by solving yield excursions. Received SMIC 2013 Continuous Improvement Competition first prize. Achieved annual yield targets one month ahead as product owner PROJECTS

Fraudsters Detection from Enron Email 02.2016 – 05.2016

Developed supervised learning algorithms to identify Enron fraudsters based on employees’ email and finance patterns. Built Naïve Bayes, Ensemble Models with Python Financial Contributions Analysis of 2016 Presidential Campaigns 02.2016 – 05.2016

Applied Exploratory Data Analysis techniques to analyze the relationship between donors’ demographics and contributions with R. Analyzed the patterns of the donation flow to reflect the status of the candidates Passengers Survival Prediction from Titanic Disaster 02.2015 – 05.2015

Applied machine learning algorithms to predict Titanic passengers’ survival

Constructed predictive models such as Logistic Regression, Support Vector Machine and Random Forest with R. Improved predictive accuracy to 82%

SKILLS & CERTIFICATIONS

Languages: R (dplyr, tidyr, ggplot2), Python (Pandas, Numpy, scikit-learn), SQL, SPSS, Matlab, Shell, Java Certification: Udacity Data Analyst Nanodegree (7 courses) and Linux Command Line Basics AWARDS

SMIC Continuous Improvement Competition first prize (1st place among 11 departments) 09.2013

Soochow University excellent graduate student (1 out of 55) 07.2008

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