Data Analytics, Mining, Modeling, Forecasting, SQL, SAS, Scripts

RAY, WAI-KWONG WONG

732-***-**** *********@*****.***

** ******* **., *********** ** 08807

OBJECTIVE

Seeking a position that utilizes my proven skill in data mining and database management analytics

EXPERIENCE

DATA ANALYST CONSULTANT, AT&T Labs, Middletown, NJ

April 2001 – August 2007, July 2009 – February 2016

Location Analysis: Delivered insight and verified the accuracy to the Network Location Model for the subscribers by WiFi, Home & Work Network data, and Geographic Latitude Longitude locations

Local Transport Data Services Analysis: Maintained and updated the monthly process by using the Billing & Local Private Lines Analytics Tools in Unix/Linux, Oracle database and Web platforms

Mobility Analysis: Categorized a key matrix in understanding the wireless (voice/data) services by comparing the monthly usage with different massive data sources:

Developed a three years forecasting model in tower and subscriber level by using the moving average and the time series regression model

Built a quantile regression model to identify the network traffic growth during peak hour

Established a churn model for the network performance by recognizing the correlations between the drop call rate and the customer disconnected rate

Migration Analysis: Constructed a customer migration model to identify the products migration (Voice, Data and Wireless) by the growth rate trend for each Signature Client Group and Small Business Market Customers

Retention Analysis: Established a customer retention model from the database management analytics to identify the risk customers and provide early warnings of disconnected customers by utilizing SAS Enterprise Miner in Decision Trees for Signature Client Group and Small Business Market Customers

Attribution Analysis: Developed and enhanced the revenue attribution model for Voice Services of massive datasets of customers in Attribution and Forecast Analysis:

Churn Analysis: Identified the key drivers of the revenue and minutes impact based on Order changing (Add / Disconnect) in Telephone Line/Billing Account level

Contract Renewal Revenue Impact Analysis: Provided contract renewal, re-pricing, and renewal revenue impact for each High End customer and identified the correlation between contract length and renewal length

Extended the analytical model on States level and developed the customer profile

Data Integration: Developed the revenue attribution model to analyze the Voice Services and Billing/Order Behavior by processing and aggregating the data in customer ID/Line levels from varied data sources, namely Data Warehouse Billing Data, Minutes Record Network Data, Monthly Contract Data and Order Data:

Generated the analytical reports by automating and streamlining from the Structural Model, such as Top add / disconnect in customer profile, Group ID level customer profile, add/disconnect identification for Billing Data, Order Data, CFO data and Sales data

Performed ad-hoc analysis with aggressive schedules

STRATEGIC ANALYST, American Express Company, World Financial Center, NY

November 2007 – January 2009

Customer Relationship Management (CRM) Strategic Analysis:

Growth Analysis: Identified the key drivers of the growth potential in 2008 of the high value small business card members who spend $1MM+ revenue annually serving with relationship managers (RMs) to drive new strategy for 2009

Spend Lift Campaign Analysis: Performed the effectiveness of the relationship managers to drive spend by statistical test design in the comparison of the test and control groups

Comparative Analysis: Concluded the RMs as the best customers across American Express by comparing the performance of the RMs to other high value small business or consumer card members without relationship managers

Authorized Account Manager (AAM) Analysis:

Deep Dive Analysis: Identified the outperforming of the marketing segmentations of the small business card members who authorize the AAMs to manage their accounts

Strategic Analysis: Developed additional insight to drive incremental spend opportunity by migrating the Non-AAM accounts to AAM accounts with High Value card members as prioritization, and to improve the end-to-end customer experience for delegate processes

Commercial Insurance Look a Like Campaign Analysis:

Segmentation Analysis: Identified the existing top forty-five card member industries, who outperform in commercial insurance spend category, as prioritized benchmark targeting campaign to change mindset/behavior of the non-insurance spend card members

Other Database Management Analytics and Aggressive Ad-hoc Analysis:

Automated & simplified the complex tasks of repetitive quarterly reporting process from the database management analytics

Statistical Test Design Read Analysis: Raw Material Inventory Upsell Campaign and Business Consultative Team Upsell Campaign

Top Merchant Spend of High Value Segments Analysis: Identified the existing top three merchants by card member industries

Key Findings for the Small Business Supply Chain Coverage Research Project:

oConcentrated(Business Spend) vs. High Share(Travel related Spend) Cash Flow Management card members

oLocal vs. Out of Town spend pattern

oHigh Wallet dominating the overall spend pattern

STAFF ENGINEER, Keyspan Business Solutions, PS&S Inc., Warren, NJ

October 2000 – April 2001

Designed HVAC systems for pharmaceutical and medical facilities with AutoCad

Assisted to coordinate a range of projects, from initial conception through completion, involving the planning, design and integration of mechanical and electromechanical systems

Reviewed preliminary and detailed engineering drawings, proposed specifications and technical plans to determine feasibility

TEACHING ASSISTANT, Department of Mechanical Engineering, New Jersey Institute of Technology, Newark, NJ

January 1996 – August 2000

Lectured the Thermodynamics course in summer 1998

Supervised and graded student homework and projects

MECHANICAL ENGINEER ASSISTANT, Manufacturing Division, Merck & Co., Inc, Rahway, NJ

January 1995

Research Project for safety examinations of pipes and pressure vessels

Examined and adjusted the ASME codes of the safety valves

Assisted the chief mechanical inspector with administration of the ASME code

PROFESSIONAL TRAININGS

SAS Enterprise Miner: Applying Data Mining Techniques, which includes Predictive Modeling, Decision Tree Modeling, Neural Network Modeling

SAS Time Series Forecasting: Using SAS/ETS Software

SAS Statistics & Report Writing: ANOVA, Regression, and Logistic Regression, A Programming Approach

Rutgers University: Applied Statistical Theory for Research

TECHNICAL SKILLS

Operating Systems: Unix(Solaris, AT&T), Linux, Hadoop, Windows NT & MS DOS

Programming: SQL, SAS, R, Pig Latin, C, Sed, Perl, Shell Script, Awk, Matlab

Database/Web Technology: Oracle, Teradata, HTML, JavaScript, Apache Tomcat

General Applications: MS Excel/PivotTable, MS PowerPoint, MS Access, MS Word

EDUCATION

Ph.D., Mechanical Engineering, August 2000

New Jersey Institute of Technology, Newark, New Jersey

B.S. Mechanical Engineering with High Honor, May 1995

Rutgers University, College of Engineering, New Brunswick, New Jersey

HONORS

Best Final Awards of 1991 at City College of New York:

Linear & Boolean Algebra

Analytic Geometry & Calculus III

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