Yu-Chen (Amber) Lu - Resume
Process-oriented Data Analyst with 3 years of experience. Proficient knowledge in Statistics, Mathematics, and Analytics. Streamlined process improvement, reducing operating costs by 50%. Identified KPIs to increase the efficacy of the compensation process by 18%. Experienced in interpreting and analyzing data using Python, R, MySQL, Advanced Excel (Pivot Table, Solver, Functions) and BI tools (Tableau, Power BI) to drive growth for industries.
EXPERIENCE
Data Developer, Jefferies LLC, New York, NY 2/2019 � 5/2019
� Coordinated with 3 teams to build a sales payout management system for business evaluation of trades by categories, which reduced operating costs by 50%
� Applied hypothesis testing to identify KPIs, increasing the efficacy of the compensation process by 18%
� Extracted, transformed, and loaded (ETL) data from MS SQL server to Qlik Sense for analyses on dashboards
� Designed, developed, and deployed data visualizations and interactive dashboards of sales payout management system for data reporting to all background users effectively
Data Analyst, Topone Information Inc., Taichung, Taiwan 8/2015 � 4/2017
� Developed, analyzed, and validated the performance of predictive models that support IT and development departments to increase 40-45% quarterly profit
� Directed weekly cross-functional team meetings as part of the forecast and sales operations improvement process
� Utilized A/B testing to identify key metrics from over 200 products, reducing 33 % operating costs
� Leveraged Python and MS Excel to optimized inventory by developing new safety stock methods to reduce the excess by 15% with no effect on service levels
EDUCATION
Master of Science in Financial Engineering, GPA: 3.93 5/2019
Stevens Institute of Technology, Hoboken, New Jersey
Bachelor of Science in Applied Mathematics 6/2015
National Chung Hsing University, Taichung, Taiwan
SKILLS
Computational: Python, R, MySQL, MS SQL Server, MATLAB, Spark, Hadoop, PostgreSQL
Business Intelligence Tools: Tableau, Power BI, MS Excel, Qlik Sense, QlikView
PROJECTS
Machine Learning: Credit Card Default Rate Prediction
� Established regression and classification models to predict credit card default rate based on cardholders� monthly payment records and historical analyses
� Performed exploratory data analysis using ggplot and conducted Bayesian Information Criterion (BIC) for determining the cross-validated prediction error on factors selection
� Implemented Random Forest method to prognosticate 82% accuracy, attaining 7% higher accuracy than Boosting, Support Vector Machine, Decision Tree, K-Nearest Neighbors, and Generalized Additive Model
Web Analytics: Financial Risk Assessment Using News
� Conducted Natural Language Processing and Sentiment Analysis to identified salient financial risks through text mining of news and increased 32% risk management efficiency
� Utilized machine learning to predict the potential impact of various news categories on each identified financial risk, and demonstrated the count/frequency of news that related to risk each month was matched with the VIX index
� Indicated that k-means clustering with multiple labels of news category had 78% accuracy, which is 6% higher than Latent Dirichlet Allocation model and Na�ve Bayes
LEADERSHIP
President, Taiwanese Graduate Student Association, Stevens Institute of Technology 1/2018 � 12/2018
� Planed, designed, and organized association schedule including 32 meetings, 14 activities, and 10 events
� Achievement: Doubled the event attendances, and tripled the membership registration rate
Captain of Orientation Leaders, Office of Graduate Student Affair, Stevens Institute of Technology 7/2018 � 8/2018
� Led a group of 20 Orientation Leaders and organized orientation for more than 2000 new graduate students
� Achievement: Received 95% positive feedbacks from the orientation participants
Process-oriented Data Analyst with 3 years of experience. Proficient knowledge in Statistics, Mathematics, and Analytics. Streamlined process improvement, reducing operating costs by 50%. Identified KPIs to increase the efficacy of the compensation process by 18%. Experienced in interpreting and analyzing data using Python, R, MySQL, Advanced Excel (Pivot Table, Solver, Functions) and BI tools (Tableau, Power BI) to drive growth for industries.
EXPERIENCE
Data Developer, Jefferies LLC, New York, NY 2/2019 � 5/2019
� Coordinated with 3 teams to build a sales payout management system for business evaluation of trades by categories, which reduced operating costs by 50%
� Applied hypothesis testing to identify KPIs, increasing the efficacy of the compensation process by 18%
� Extracted, transformed, and loaded (ETL) data from MS SQL server to Qlik Sense for analyses on dashboards
� Designed, developed, and deployed data visualizations and interactive dashboards of sales payout management system for data reporting to all background users effectively
Data Analyst, Topone Information Inc., Taichung, Taiwan 8/2015 � 4/2017
� Developed, analyzed, and validated the performance of predictive models that support IT and development departments to increase 40-45% quarterly profit
� Directed weekly cross-functional team meetings as part of the forecast and sales operations improvement process
� Utilized A/B testing to identify key metrics from over 200 products, reducing 33 % operating costs
� Leveraged Python and MS Excel to optimized inventory by developing new safety stock methods to reduce the excess by 15% with no effect on service levels
EDUCATION
Master of Science in Financial Engineering, GPA: 3.93 5/2019
Stevens Institute of Technology, Hoboken, New Jersey
Bachelor of Science in Applied Mathematics 6/2015
National Chung Hsing University, Taichung, Taiwan
SKILLS
Computational: Python, R, MySQL, MS SQL Server, MATLAB, Spark, Hadoop, PostgreSQL
Business Intelligence Tools: Tableau, Power BI, MS Excel, Qlik Sense, QlikView
PROJECTS
Machine Learning: Credit Card Default Rate Prediction
� Established regression and classification models to predict credit card default rate based on cardholders� monthly payment records and historical analyses
� Performed exploratory data analysis using ggplot and conducted Bayesian Information Criterion (BIC) for determining the cross-validated prediction error on factors selection
� Implemented Random Forest method to prognosticate 82% accuracy, attaining 7% higher accuracy than Boosting, Support Vector Machine, Decision Tree, K-Nearest Neighbors, and Generalized Additive Model
Web Analytics: Financial Risk Assessment Using News
� Conducted Natural Language Processing and Sentiment Analysis to identified salient financial risks through text mining of news and increased 32% risk management efficiency
� Utilized machine learning to predict the potential impact of various news categories on each identified financial risk, and demonstrated the count/frequency of news that related to risk each month was matched with the VIX index
� Indicated that k-means clustering with multiple labels of news category had 78% accuracy, which is 6% higher than Latent Dirichlet Allocation model and Na�ve Bayes
LEADERSHIP
President, Taiwanese Graduate Student Association, Stevens Institute of Technology 1/2018 � 12/2018
� Planed, designed, and organized association schedule including 32 meetings, 14 activities, and 10 events
� Achievement: Doubled the event attendances, and tripled the membership registration rate
Captain of Orientation Leaders, Office of Graduate Student Affair, Stevens Institute of Technology 7/2018 � 8/2018
� Led a group of 20 Orientation Leaders and organized orientation for more than 2000 new graduate students
� Achievement: Received 95% positive feedbacks from the orientation participants