SUMMARY

• Extensive industry analytics experience using statistical analysis and predictive modeling.
• Specialize in the area of revenue management, pricing, reporting, segmentation, customer targeting, and market forecasting, etc.
• Proficiency in SAS (Base, Stat) and SQL programming, Excel, Access, Cognos, PowerPoint.
• Predictive modeling experience in linear and logistic regression analysis.
• Strong background in statistics and mathematical optimization, forecasting, and simulation, etc.
• Demonstrated strong analytical skills and problem-solving skills with superior attention to detail.
• Proven ability to manage multiple projects with excellent organization skills.
• Ability to work independently and cross functions in a timely manner.
• Effective communication, written and presentation skills.
• High capability to quickly learn new technology and adapt to a new environment.
• US permanent resident.

Professional Experience

Confidential, PHILADELPHIA, PA 2009 - Present
SENIOR STATISTICAL ANALYST – REVENUE MANAGEMENT
Supported revenue management using statistical and quantitative analysis, developed several statistical approaches and optimization models to save more than half million $ in program cost and by price distribution, designed and significantly enhanced monthly contract renewal process, created and managed several important pricing performance reports, performed various ad hoc analyses posed by key stakeholders, and provided data-driven actionable recommendations for the business.

• Designed and developed a novel pricing distribution summary to help SCA avoid a potential financial loss of more than half million $.
• Created an accurate visual summary of Into-stock and contract price distribution by removing outliers, identifying extremely low price and resolving other pricing data issues.
• Enabled senior management to find the right price for the product and make a better decision.
• Manipulated large transaction databases using SAS programming and SQL.
• Built a new mathematical model and price approach for strategic partner to avoid a potential $90k program loss plus additional cost savings
• Successfully provided Gordon Food Service USA a new price strategy to simplify various programs using an optimization model.
• Accomplished an innovative monthly contract renewal process using SAS to significantly reduce the process time from 23 hours to 30 min
• For the first time utilized SAS programming to conduct contract renewal process starting from scratch within a tight deadline.
• Added critical information like recommended price for each product with different customer, net margin, case volume, and price guideline, etc.
• Significantly improved process speed, accuracy, reliability, and transparency.
• Developed and managed pricing reports to make accurate compensation for sales professionals
• Successfully created net price weekly and monthly reports to separate national account sales from field sales accounts for the 1st time.
• Managed monthly Into-stock pricing and Contract pricing reports for the field.
• Provided reliable pricing performance reports for the sales force to track trends, identify business opportunities, and get accurate compensation.
• Created a predictive model to help price management to set up the appropriate product price
• Predicted price elasticity relationship between price and case volume using SAS regression.
• Provided insights and make actionable recommendations for price management.

Confidential- InTERN 2008 -2009
Statistical Modeling and Database Analytics
Provided analysis, modeling and programming support to help Conde Nast to make a better decision for the business, like how to optimally allocate promotional resources, how to enable targeted mailing by identifying responders, how to reduce cost by suppressing non-responders, etc.

• Performed data analysis using customer individual level databases with over 70 million records.
• Developed logistic regression models to predict subscription response rate based on customers’ variables like past transactions, response to prior mailings, promotions, demographics, interests and hobbies, etc.
• Extracted and integrated primary dataset, conducted variable selection using stepwise procedure.
• Developed cluster analysis to create customer behavioral segmentations.
• Identified trends and patterns in business results and made recommendation for future campaign.
• Created result reports for model performance using MS Excel, Pivot Tables, and Engage.

Education
M.S in Operations Research, 
PhD in Physical Chemistry (involving quantitative analysis and mathematic modeling),

SOFTWARE SKILLS

• Data Analysis: Base SAS, SAS/STAT, SAS/MACRO, SAS/SQL, SAS/GRAPH, Excel, VBA, JMP, MS Access
• Optimization and simulation: Excel Solver, LINDO, Pro Model, Neural Networks
• Operating systems: Windows, UNIX

RELEVANT ACADEMIC COURSES

• Applied Data Base Management using SAS · Logistic Regression
• Regression Analysis & Econometrics · Statistical Research Methods
• Probability Theory and Random processes · Design and Analysis of Experiment
• Deterministic and Probabilistic Modeling · Optimization Modeling with Spreadsheet