SUMMARY

• More than 8 years of experience in data analytics, analytical reporting, statistical modeling and credit risk management in Banking and Insurance domain. Subject matter expert (SME) in programming, development and reporting using SAS, MS SQL, Tableau and advance Excel
• Experience in data validation, profiling, quality, migration, visualization, integration and verification
• Good understanding of Basel II, CCAR/ Dodd - Frank (DFAST) stress testing concepts in retail & commercial banking including probability of default (PD), exposure at default (EAD), loss given default (LGD), expected loss (EL), and risk weighted assets (RWA) etc.
• Experience in credit risk modeling including PD and loss forecasting model development
• Good experience in risk regulatory reporting predominantly focused on Basel II, CCAR/ DFAST stress testing regulations
• Experience and expertise of Banking and Insurance products such as Credit Cards, commercial loans, and Home/ Auto Insurance
• Basic noledge of Balance sheet and Profit & Loss (P& Confidential ) statements
• Hands on experience in data modeling using linear, logistic regression and time series techniques
• Good experience in running SAS programs on Mainframe and Unix servers
• Extensive hands on experience in analytics and reporting using Base SAS, SAS/Enterprise Guide(EG), SAS/MACRO, SAS/GRAPHS, SAS/ACCESS, SAS/CONNECT, SAS/SQL, SAS/Visual Analytics(VA), SAS/Data Integration (DI) Studio and SAS/Business Intelligence (BI)
• Advanced skills on data cleansing, manipulation and statistical analysis using SAS procedures such as PROC SUMMARY, PROC SORT, PROC FREQ, PROC MEANS, PROC UNIVARIATE, PROC FORMAT, PROC TRANSPOSE, PROC PRINT, PROC CORR, PROC LOGISTIC, PROC REG, PROC GLM and many SAS data steps like ARRAY, MERGE, SET etc.
• Good command in producing tables, listings, and reports (HTML, RTF, PDF) employing SAS procedure steps such as SAS ODS, DATA NULL, PROC REPORT, and PROC TABULATE according to teh requirement.
• Implemented logical statements such as IF/ELSE, SELECT, WHERE to streamline teh data processing and preparing reports quickly.
• Experience in bringing large data from SAS and non-SAS data sources into a SAS environment and performing SAS data manipulations against teh resulting sets. dis includes ability to merge datasets and to write SAS Macros and generate list outputs/reports.
• Good command in importing and exporting complex internal data to and from Microsoft Excel, Microsoft Access, Oracle and CSV using SAS IMPORT/EXPORT Wizard, PROC IMPORT, PROC EXPORT and SQL Pass-Through facility
• Experience working in SAS BI platform with Stored Process, Microsoft Add-In, Information Map Studio and DI Studio
• Used MS Office (e.g. Excel - vlookup; hlookup etc., Pivot table, PowerPoint, Word), PROC GPLOT, PROC GCHART and Tableau to create effective visualization and presented data driven insights to management
• Good experience in SQL joins (left join, right join, inner join, full join etc) and constraints
• Extensive experience in requirement analysis, design, application development, programming, testing, implementation, and coordination with senior management

TECHNICAL SKILLS

Platform: Windows, UNIX, Mainframe

Languages: SAS, SQL, DB2

Analytics/Statistical Packages: SAS v9.2/v9.3 (Base SAS, SAS/EG, SAS/VA, SAS/SQL, SAS/MACRO, SAS/ACCESS, SAS/GRAPHS, SAS/ODS, SAS/SQL, SAS/REPORT, SAS/CONNECT, SAS/BI, SAS/DI Studio), Tableau

Databases: SQL Server, Oracle

Application Software: MS Word, Advance Excel, MS PowerPoint

PROFESSIONAL EXPERIENCE

Confidential, New York, NY

Responsibilities:

• Building Basel II PD model using logistic regression. It includes preparing term of reference (TOR) document, extracting data from Citibank internal databases, performing data quality checks (DQC), data scrubbing & reconciliation, creating new variables, segmentation and sampling, converting continues variables to categorical by creating bins (fine classing), customize bins (Coarse classing), variable reduction using information value (IV); stepwise selection methods; cluster and correlation analysis, segmentation, sampling, developing & finalizing teh model and model validation
• Carrying out customer credit history data extraction from Citibank credit card database and other sources using SAS PROC IMPORT, SQL PASS THROUGH FACILITY and LIBNAME.
• Summarizing raw dataset and performing data parsing using SAS procedures such as PROC SQL, PROC SUMMARY, PROC TRANSPOSE, PROC MEAN, PROC CONTENTS, PROC FREQ, PROC SORT and SAS data steps like ARRAY, MERGE, SET etc.
• Using logical statements such as IF/ELSE, WHERE and other SAS/SQL statements to create new variables, segmentation and out of time sample
• Creating in-time validation sample using PROC SURVEYSELECT
• Creating fine classing and coarse classing using PROC FORMAT, PROC FREQ etc. and calculating weight of evidence (WOE) and information value (IV) for each model variables
• Using PROC CORR and VIF to check correlation between teh variables
• Creating variables clusters using PROC VARCLUS
• Developing PD model using PROC LOGISTIC in SAS
• Calculating PSI & VDI for model stability, KS & GINI for model discrimination power and Chi-Square for model accuracy
• Validating new model on in-time and out of time validation samples
• Presenting model output to project manager and senior management and get their approval
• Working on model documentation for senior managers and regulators which includes details of portfolio, methodology and model development process
• Plotting frequency distributions of predicted probability of loan default histogram by PROC GPLOT and GHART.
• Estimating Regulatory capital, RWA and EL using probability of default calculated using logistic regression and given EAD and LGD.
• Summarizing teh result and report to senior modeler by PROC REPORT, PROC FORMAT, PROC TABULATE and SAS ODS
• Develop credit loss forecasting models and generate reports using SAS Visual Analytics

Environment: Windows, SAS 9.3, logistic regression, Basel II, PD, EAD, LGD, EL, RWA, Base SAS, SAS/EG SAS/Macro, SAS/GRAPH, SAS/ODS, SAS/SQL, SAS/VA

Confidential, New York, NY

SAS/SQL Credit Risk Analyst

Responsibilities:

• Analyze Confidential wholesale banking portfolios including Global Banking, Commercial Banking & Private Banking customers
• Project includes risk regulatory report preparation during CCAR & DFAST stress testing process, and stress models implementation using SAS, MS SQL, Tableau and advance Excel etc.
• Work includes designing reporting framework, gathering business requirements, dealing with different stakeholders for data extraction; model outputs; CCAR & DFAST scenarios; generating analytical reports, model implementation and UAT etc.
• Calculating RWA and stress capital for baseline, adverse and severely adverse scenarios
• Extract live portfolio from internal systems where information is stored in Oracle tables using SAS IMPORT/EXPORT WIZARD in SAS environment
• Extract data to and between remote server to PC environment using PROC UPLOAD and PROC DOWNLOAD
• Perform data validation, data cleansing using different procedures such as PROC MEANS, PROC FREQ, PROC SORT, PROC CORR etc.
• Merge SAS datasets using various SQL joins such as LEFT JOIN, RIGHT JOIN, INNER JOIN and FULL JOIN as well as using SAS procedures such as SET and PROC APPEND etc.
• Analyze data using PROC UNIVARIATE, PROC SUMMARY, PROC FREQ, PROC RANK etc.
• Create analytical reports using PROC REPORT, PROC TABULATE, PROC SUMMARY, ODS statements and generating outputs in HTML, Excel, RTF and PDF formats
• Import all Reports using Stored Process, BI Dashboard and Information Map to Information Delivery Portal
• Develop ETL code using SAS DI Studio to create SAS tables and views.
• Migrate SAS codes and Libraries between different versions and between DEV, UAT and Production
• Develop SAS Macro programs and using macro functions (%LET, CALL SYMPUT, %NRSTR, SYMGET etc.) to reporting processes to improve process efficiency and provide more meaningful information vital to teh overall strategies
• Create dynamic Macro arrays by SQL and with SAS data step programs
• Implement stress models in Confidential systems and perform user acceptance test (UAT)
• Extensive usage of MS office and teh functionality of excel such as lookups, macros, statements etc.
• Designing and developing Tableau visualizations which include preparing Dashboards using calculations, parameters, calculated fields, groups, sets and hierarchies.
• Perform approvals for peer audit reviews on reports by analyzing data

Environment: SAS 9.2, MS SQL Server 2003/05/08, SAS/Base, SAS/MACRO, SAS/ACCESS, SAS/DI, MS Word/ Excel, Oracle, CCAR

Confidential

SAS/SQL Credit Risk Analyst

Responsibilities:

• Develop and monitor roll rate based loss forecasting models using time series techniques for different credit card portfolios across Confidential Bank, USA
• Extract data from different sources like Oracle database, Excel, Access, and text/CSV files using PROC IMPORT/EXPORT and SQL Pass-Through facility in SAS environment and creating SAS files
• Perform data quality checks, data cleansing, data reconciliation with different teams at different levels using PROC MEANS, PROC FREQ, PROC SORT, SET, MERGE etc.
• Create in-time validation data using RANUNI function in SAS
• Develop credit loss forecasting models to forecast key KPIs in risk management such as provisions, LICs, charge-offs etc.
• Validate models on in-time and out of time validation samples
• Work on model documentation for senior management and regulators
• Coordinate with different stakeholders and presenting estimates at regular intervals
• Develop analytical reports using PROC REPORT, PROC TABULATE, ODS statement and present detailed view of different portfolios at different levels to senior management for key decision making
• Analyze risk data using PROC UNIVARIATE, PROC SUMMARY, PROC FREQ, PROC CORR, PROC RANK, PROC TRANSPOSE etc.
• Develop SAS MACRO programs to automate different modeling and reporting processes to improve process efficiency and provide more meaningful information vital to teh overall strategies
• Develop repetitive loops for retrieving ARRAY variables for joining of datasets for ad-hoc reporting
• Perform analyses, development and evaluation of data/reports in a data warehouse/enterprise environment which includes data requirements

Environment: SAS 9.0, MS SQL Server 2008, Oracle, SAS/BASE, SAS/MACRO, SAS/ACCESS, SAS/VA, MS Word, Excel, Time Series

Confidential

Data/BI Analyst

Responsibilities:

• Worked as an inevitable resource supplying basic raw data for teh different risk teams
• Create daily, weekly and monthly ACV data mart to derive NII, NFI, credit card sales, outstanding balance, defaults etc
• Involved in Data Mapping efforts with detailed understanding of teh database structure
• Extract data from Oracle database using PROC IMPORT, SQL Pass-Through facility in SAS environment and create SAS files
• Design several ETL jobs using SAS DI Studio to port teh ODS data into data marts with tasks involving configuring metadata libraries in SMC, developing transformation logic and staging teh final data
• Perform data validation, cleansing and reconciliation with historical patterns and other teams
• Develop analytical reports using PROC REPORT, PROC TABULATE, SQL procedures and present detailed view of different portfolios at different levels to senior management for key decision making
• Develop SAS MACRO programs to automate different modeling and reporting processes to improve process efficiency and provide more meaningful information vital to teh overall strategies
• Develop repetitive loops for retrieving array variables for joining of datasets for ad-hoc reporting
• Coordinate with different stakeholders and presenting estimates at regular intervals
• Optimize teh monthly Debits Card transactions data mart by implementing new logics and reduced turnaround time by 8 hrs
• Create dynamic Macro arrays by SQL and with SAS data step programs
• Actively involved in different kind of SQL queries for matching of teh data.

Environment: SAS, PL/SQL, SQL Server 2003, Mainframe, Oracle, SAS/BASE, SAS/MACRO, SAS/ACCESS, SAS/DI Studio

Confidential

Data Analyst

Responsibilities:

• Analyze teh specifications provided by client
• Create software requirement specifications in collaboration with business analysts
• Develop SAS and SQL programs for analyzing insurance data and generate meaningful insights
• Prepare detail design document
• Work on Application development & Programming & Testing

Environment: SAS (Base SAS, SAS/SQL etc.), MS SQL, Mainframe COBOL, JCL, IMS DB, DB2, FILE AID, COOL: GEN