Yujen (Warren) Wang

Atlanta, GA, ***** / 469-***-****/ adjbls@r.postjobfree.com / www.linkedin.com/in/warren-wang Profile:

Skilled data scientist with 4+ years of experience in marketing and revenue management domains. Strong passion to prove assumptions about customers at your organization with machine learning, deep learning, statistic, automated algorithms, and other fun tools.

EDUCATION:

The University of Texas at Dallas, M.S., Business Analytic focus on Data Science - Dean’s list / Dallas, Texas / 2020 National Chengchi University, B.S., History / Taipei, Taiwan / 2014 Professional Experience:

Revenue Analyst

PARK ‘N FLY Airport Parking, Atlanta, Georgia Jan 2020 – Oct 2020 Constructed automated revenue forecast system for 17 parking lots, utilized time series analysis on 5 million transactions to identify customers’ booking and exiting pattern, automated the pricing system with statistics support.

• Data Pipeline: Created data pipeline on transactional database to automate reporting process; Graphically summarized consumers behavior in 10 years' transactions to C-levels.

• Data Mining: Leveraged statistical models to detect and quantify booking abnormality in 17 lots and attribute revenue surge to time series features.

• Time Series Analysis: Statistically support revenue director when reporting budget to stakeholder; Applied statistical models to isolate and quantify seasonality and trends in weekly revenue of individual lot.

• Machine Learning: Automated budget generating process at the same time maintain accuracy on revenue forecast with xgbar, Prophet, H2O, RNN; Reached 93% accuracy; Reduced budget generating time from a month to a week. Marketing Analyst

TRENDYOUNG Marketing Corp., Taipei, Taiwan Jul 2014 – Aug 2018 Generated 1 million revenue for our agency by executing channel marketing for Fortune Global 500 companies, self- taught analytics skills to utilize data-driven strategies in off-line marketing campaigns.

• Project Management: Owned 500+ CPG&CE campaigns on digital and brick/ mortar channels, training 1000+ part- timers, reporting metrics to 13 clients and creating robust communication with 7 retailers.

• Unsupervised Learning: Clustered transactions to create segmentation metrics by K-means, SOM and performed descriptive analysis with Excel VBA; Reduced cost on training part-timers by 7%; Increased sales by 12%.

• Data Collecting: Build data entities to store up-to-date competitors' price by web scraping and field investigations with selenium and Tableau; Enhanced agency's information richness when designing campaigns with clients. TECHNOLOGY SUMMARY: (Recently used)

• Software: R, Python, SQL, PowerBI, SAS, Tableau, Excel, GitHub, Google Analytic/ Data Studio

• Package: Scikit-learn, Keras, Pytorch, Feature-Engine, data.table, tidyverse

• Model / Algorithm: SARIMAX, h2o, Prophet, XGBar, SGD, RNN, SVM, Tree-based, Regressions, Softmax, LDA, Bayesian methods, K-mean, SOM, Apriori, Kernel PCA, Thompson Sampling, KNN, Ensemble Learning

• Analysis: Life-time Value, Price elasticity, Time-series Analysis, Bayesian A/B testing, Market Basket Analysis