Project Manager Data Analysis

Boren Xu

530-***-**** *****@*******.*** linkedin.com/in/borenxu Davis, CA

OVERVIEW: A dynamic, entrepreneurial and driven young professional seeking a fulltime role in business or data analytics following upcoming graduation. Advanced academic and practice expertise across data science, machine learning, and business operations.

EDUCATION:

University of California, Davis

Bachelor of Science in Statistics, Anticipated Jul 2018 (3.7/4.0 Major GPA)

Relevant Coursework: Statistical Data Science (R), Data & Web Technologies for Data Analysis (Python), Regression Analysis, Analysis of Categorical Data, Operations Research and Management Science

Awards: Dean’s Honors List – Winter 2011/ Spring 2011/ Fall 2017

SKILLS:

Technical Skills: SQL, R, Python, Git, Markdown, Machine Learning, Data Analysis, Data Visualization

Language: English; Mandarin (native)

WORK EXPERIENCE:

Compass Network Technology Co., China 2014 – 2017

Co-Founder Project Manager & Product Manager

●Conceptualized, built, co-founded and managed Compass Network Technology Co., a one-stop corporate travel platform to enhance the business travel experience

●Researched, developed, pitched and finalized the booking platform design

●Secured $3.5M in series A funding, resulting in growth of 100 employees and $20M in gross merchandise volume

●Supervised the development team of 20 software engineers and delivered 2 new version updates every week

●Actively analyzed and evaluated the data of daily transactions associated with business operations and KPIs

●Exited in 2017 to resume undergraduate studies at UC Davis

SELECTED PROJECTS:

Shopping Website Revenue Optimization (R) (Feb 2018)

●Targeted 3-month-dormant one-time buyers to incentivize them to purchase again through the development of a strategic marketing program

●Utilized R to conduct data imports, clean and preprocess and perform model tuning and optimization

●Successfully improved the program efficiency with machine learning models by at least 80% compared to baseline methodology on back testing, with over 2GBs of training data processed on single machine

●Implemented classification models, including Lasso logistics regression and Random Forest, with Cross-Validation optimization

IOS Store Monetization A/B Testing Experiment Design (Python) (Jan 2018)

●Conducted exploratory analyses on longitudinal user data (0.6M unique users and 15+ dimensions) in Python, resulting in the discovery of strong correlation between user conversion and form of payment used

●Identified potential monetization opportunity to improve buyer conversion rate and boost revenue by 11.48% by incentivizing user to purchase or add digital gift cards

●Designed and launched A/B testing experiment to determine possible revenue uplift by offering monetary promotions to 5% of new buyers

●Built an interactive and scalable Python dashboard to measure impact of experiments through Jackknife confidence intervals and the calculation of statistical significance

KNN Algorithm for Classifying Handwritten Digits in Zip Code (R) (Dec 2017)

●Built machine learning algorithm, K-Nearest Neighbor, from scratch to predict the label of digits for collection of points in R

●Performed Cross-Validation optimization (Reducing running time by 85%) to estimate misclassification error rates for different value of K (0 to 15) for prediction

●Evaluated best Ks and distance metric combination with confusion matrix

Analysis of Bike-Sharing Trending in Major Cities (R) (Nov 2017)

●Examined the number of trips at various time periods, magnitude of distances and duration of owning bikes in San Francisco and Los Angeles

●Summarized data using graphical analysis to identify patterns and attribute possible reasons to the research results

●Analyzed biking directions during various times of the day to forecast rider purpose

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