Led enterprise-wide strategic initiatives that drive innovative transformation through big data tools and platforms, along with advanced analytics and machine learning.Led the efforts for establishing an Enterprise Analytics Center of Competency within Walmart ISD's Enterprise Information Management pillar. Built up onshore and offshore Analytics teams to provide enterprise analytics services within Walmart, including analytics infrastructure/tools/data services, analytics delivery center, exploring and conducting proof of concepts on emerging analytics technology and methods, along with end-user support and enablement.

Provided enterprise shared services, ranging from predictive model development and implementation, direct marketing strategy development and operations, third party data assessment and acquisition. Led the efforts to revamp existing debt recovery models for Call Center Collection and to develop new recovery propensity model as well as netback forecasting model for Legal Collection.Partnered with TransUnion to build a pre-purchase pricing model and portfolio evaluation tool in order to reduce variances of portfolio underwriting.Developed model validation process and model performance monitoring mechanisms to ensure model accuracy, robustness, and compliance. Collaborated with IT, Call Center Collection, Legal Collection and third party data providers to drive testing and execution of models. Led the development of direct marketing data mart to improve accuracy and efficiency of campaign planning and turnaround time of post-campaign analytics. Provided ongoing analytic support for cross-functional areas pertaining to collection performance. Led the efforts to evaluate and procure third party data that are essential to improve debt collection effectiveness. Upgraded enterprise-wide analytics tool sets by negotiating multi-year contract with SAS that includes SAS Enterprise Guide, SAS Access to Microsoft Office, SAS Enterprise Miner and a free trial of SAS Text Miner.

Led major enhancements for GM’s global IT asset management tool previously built as a proof of concept. Successfully implemented major enhancements on time within budget, resulting in improved usability and wider end-user acceptance//utilization globally. Defined and maintained operations process and procedure guidelines in support of GM’s global IT asset and lease management (ITALM) function.Worked with cross-functional GM stakeholders and Performing Suppliers to improve ITALM processes and operating guidelines.Accountable for all aspects of the ITALM tool activities ranging from application development, operations support, and ongoing sustain activities.Developed next-generation strategy for managing IT assets and leases.

Led a team of analysts and data specialists to provide analytics services to various business units within OnStar, including Subscriber Relationship Marketing, Wireless Sales and Marketing, XM Sales and Marketing, and Service Delivery Operations.Expanded analytics services to support additional OnStar business units with advanced analytics capabilities.Hired, coached, and mentored analysts and data specialists on OnStar business, subscriber life cycle management methodology, OnStar database schema, and business rules associated with data extraction.Implemented SAS/Business Intelligence platform to streamline campaign analytics and reporting processes with faster turnaround time.Adjusted timing and frequency of post-campaign measurements to enable stakeholders to make informed decisions at a faster speed. Reduced departmental budget by more than 30% with increased staff quality and throughput.Reduced Up for Renewal (UFR) data cube creation cycle time by 90% to provide timely UFR analysis for stakeholders.Led the analytics efforts to gain better understanding of OnStar’s impact to GM vehicle owner loyalty.

Established and ramped up program management office for Global Media Asset Exchange (MAX) initiative. Consolidated media assets across multiple divisions and multiple advertising agencies for GM. Managed the operations of GM Media Archives, including taxonomy structure, asset tagging and classification, system enhancements, and customer services. Managed global deployment of WebEx as GM's web collaboration tool to save costs and improve efficiency.

Managed the development of an award-winning collaboration web site to support GM's auto show events globally. Established the first web site testing lab at GM to ensure appropriate rendition of GM's consumer facing web sites.

Participated in the specification and design for Phase I of the Customer Management System (CMS): gathered business requirements as inputs to the construction of the CMS data models; and interviewed GM legacy system owners to develop data sourcing and mapping requirements.Managed the Phase I User Acceptance Test (UAT) activities for CMS, including developing test plan and test cases, coordinating execution of UAT test cases and compiling summary report of UAT results.Established and managed the Data Quality Assurance Task Force to implement procedures and processes for continuous improvement of data quality in CMS. Managed EDS support group to provide ad-hoc and routine reporting and analytical support to the BRM team.Developed RFP and selection criteria for third-party data purchases for CMS. Worked with Worldwide Purchasing on vendor selection and contract negotiation. Conducted interviews with external data providers and analytical tool suppliers to identify best practices of analytical and reporting methods to support GM’s enterprise customer management (ECM) initiatives. Managed the selection of analytical tools for ECM and the start-up of ECM's analytical capabilities.

Developed cross-selling models to identify the next best product to offer to existing customers that will maximize the probability of the product being sold and increase Comerica’s profitability.Conducted statistical profiling analysis for commercial customers and prospects using internal account information from various processing systems and external firmographic data from Dun & Bradstreet to support marketing initiatives of Corporate Banking unit. Provided technical assistance to Direct Marketing Managers and business unit managers in the development of predictive models for acquiring new home equity customers. Developed statistical models to predict expected profitability for small business prospects, which was used as the basis for small business market segmentation. Developed predictive attrition models for retail and small business DDA customers, applying attrition risk scores from the models to identify at-risk profitable customers and recommending targeted retention strategies based on modeling results. Produced Retention Journal to assist customer retention campaigns. Participated in the development of small business credit scoring models.Evaluated and beta-tested SAS Enterprise Miner and Urban Science’s GainSmart in order to shorten the time frame of predictive modeling process.Created data mart from different sources of Comerica to increase the efficiency of database modeling.

Improved operational efficiency and effectiveness by working with Dun & Bradstreet and Experian to revamp Sanwa’s risk-rating scorecards that increased the threshold of dollar amounts for automated processed transactions but not raising the level of risks to Sanwa. Provided technical assistance to Portfolio Management to explore alternatives for portfolio scoring and monitoring, behavior scoring and collection scoring. Provided training to staff members on credit risk modeling techniques.

Participated in the design and implementation of Customer Information System (CIS) Phase II, which links CIS with health care utilization and provider network information. Responsibilities included business requirements gathering, prototype review, data sourcing, data mapping and data transformation.Participated in CIS Phase I enhancement to improve its data quality and integrity.Conducted churn/penetration/retention analysis on BCBSM’s customer base. Used SAS and MS Access to generate customer information reports from CIS. Used MS Access and Visual Basic to develop a reporting sub-system from the Prospective Customer Qualification System (PCQS) to support the marketing efforts of Michigan Sales and Services toward BCBSM’s prospective customers.

Utilized Polk's proprietary databases to perform a variety of market segmentation analyses for automotive industry, including buy rate analysis, car buyer profile analysis, single factor analysis, sales match, and logistic regression modeling. Teamed up with Polk’s Sales Associates to serve clients needs in project scheduling, project design consultation, and interpretation of research results.Provided training to Performance Analysts on SAS programming and multivariate statistical methods.

Developed credit risk scoring models for automotive retail and leasing business of Ford Credit US and Canada. Using advanced SAS programming skills (SAS Macro, Arrays, Proc IML) to incorporate spline smoothing techniques into variable selection process that reduced cycle time for variable selection from weeks to hours.Augumented baseline logistic regression models with the Heckman two-stage modeling approach to correct the selection bias inherent in modeling sample selection. Research new scoring criteria varialbe from Credit Bureau data to iprovie predictive power of the exiting credit risk scoring models.

Utilized SAS to build a monthly forecast monitoring system with automated statistics reports that improved departmental efficiency in providing information for management reports and decisions.Developed SAS routines to maintain monthly oil price databases and utilized time-series forecasting techniques to develop models for oil price forecasting. Provided statistical and programming assistance in different stages of long-range demand forecasting. Participated in the preparations of various departmental annual reports and the development of industrial demand modeling.