Managing credit risk strategies for First Mortgage, Heloc and Auto

•Lead & mentored a high-performing global team of 6+ data analyst focused on statistical data analysis and reporting with valuable insights and trends to drive business operational efficiency up-to 1MM/Year by combating counterfeit, addressing copyright violations & eradicating spam on FB and IG platform globally•In partnership with data scientist and engineers, deployed multiple proactive data solution via experimentation and four machine learning classifiers, improving the accuracy over 40% in less than 12 months and saving up to $2MM per year in recurring savings •Spearheaded the overall META payment platform to determine credit risk & fraud with remediations as necessary to influence policy changes and meet regulatory & compliance requirements•Working with multiple business teams( Director & VP) to formulate their business, analytical andreporting need, and proposed critical KPI to measure the success and efficiency of the business•Lead the effort to simplify Organization level OKR & Roadmap and propose strategic growth plans fordata analytics teams in conjunction with XFN partner :product , operations , ML engineer and DS teams

•Made an impact to improve business profitability by 5% by recognizing the most profitable customer and product segment , where as weeding out the least profitable ones. •Improved the ROI by 2% on dollars spent by accurately pricing each deal, and expanding our foothold in the industry. •Being an SME for the Transportation business, lead multiple projects to improve data quality across the organization which has helped improved all stakeholders confidence in our data, reduced the time and effort to reconstruct by 40%,and making it ready to mine for actionable insights on tableau/qlickview. • Lead the team to develop an automated model monitoring with statistical KPI's to identify any risky behavior and flag them for risk mitigation to meet regulatory compliance. • Using SAS SQL, developed multiple modeling data sets for NLP, originations and behavioral models, and performed extensive bureau validation on regular basis , analyze data streams using statistical methods and report recommendations to senior Risk leaders.

-Successor to GE capital TF business.• An SME for all data underlying TF portfolio for performance, default , application and bureau data.• Implemented automated model monitoring for model performance, validation and annual assessment with Risk Leaders of Origination, PD and LGD models.• Developed Modeling data sets for Origination/PD models , validating bureau data using SAS/BASE, SAS/STAT, SAS/MACRO and SAS SQL, and report recommendations to senior Risk leaders.•Continue to improve / develop/maintain trend reporting and forecasting rolling delinquency of Tranportation Finance portfolio •Working proactively and closely with risk analytics managers and the finance department to validate , consolidate, and improve business risk analytics and data gathering process

•Developing risk models, PD and LGD, in Enterprise Miner to automate model development.•Implemented model monitoring for performance and validation in SAS Model Manager.•Developing process structure around DI studios to address data lineage and drive standardization to support model management framework.•Automated the LGD and PD modeling code to produce ongoing monitoring using SQL/SAS macros. •Developing analytical data marts for business across GE Capital.

Hired by C-suite of financial services firm to build risk assessment modeling, analytics, & reporting infrastructure to report back to CEO.• Implemented underwriting rules using Decision Trees for loan approvals which reduced the First Payment default by 33 % , minimizing reduction in population by < 27% and improving Return On Loan by 10% over 360 days.• Developing Logistic Regression model to assess underwriting risk .• Designed, analyzed and manipulated SAS data sets, including data extraction to SAS from TEXT and CSV files, analysis of data in SAS, and generating diverse reports using SAS/BASE, SAS/SQL, SAS/MACROS.• Improved response rate via Statistical T-testing for marketing department .• Analysis, trending and projections used to assist in securing additional investment capital for growth.• Working with data vendors to back test loan performance with alternative data sources• Implemented AWS(Amazon Web Services) for our Reporting & Modeling suite in less than 45 days.• Implemented new reporting delivery system by switching daily emails to online Dashboards and further implementing Tableau for interactive services.

• Developed an automated system to increase the efficiency to execute larger number of campaign.• Performing data processing for the execution of the complex marketing campaign using Unix, SAS, and Teradata/Oracle/DB2 Databases. • Develop code based on technical specifications to extract and process targeted account data. Validate and test all code for accuracy and efficiency. • Report and track defects in Test Director/Quality Center. Creating and troubleshooting automation scripts for adaptation for new testing• Developing automated system to resolve Production issue effecting millions of customer using Aprimo ,Sharepoint , Infopath and QC

• Used SEO to increase traffic from 20 % to 40 % in 3 months with 5% increase in unique visitors .• Produced reports and performed data massaging , using various SAS macros.