SUMMARY

• Analytical professional with 7 years of advanced hands on experience in BASE SAS, SAS EG, SAS Studio, SAS SQL and SAS Macros, both at UNIX and Windows environments.
• Solid working experience in designing, redesigning and calibrating strategies by analyzing P&L and historical data at various industries like financial institutions, e - commerce, pharmaceuticals, telecommunications, federal government and academic institutions. Newly designed strategies reduced losses up to 42%.
• Heavy use of SAS experience on a daily basis, for analysis of enormous data sets, frequently including millions of transactions characterized by hundreds of variables. Integrated SAS output with Excel to efficiently generate weekly/monthly automated reports or ad-hoc analysis, for senior management.
• Data extraction, cleaning, analyzing, graphing and reporting using SAS procedures such as SQL, REPORT, TABULATE, MEANS, SUMMARY, SGPLOT, etc.
• Strong business knowledge with quantitative research skills, capability in understanding various data structures, efficient problem solver, fast learner with excellent communication skills.
• Extensive experience in working with senior management and cross-functional teams, presenting analysis results to both technical and non-technical audiences.
• Specialties: Risk Management, Data Mining, Loss Mitigation, Credit Management, Fraud Analytics and Reporting, Customer Segmentation, Decision Trees, Scoring, and Customer Analytics.
• U.S. Citizen with Public Trust (MBI) clearance.

TECHNICAL SKILLS

Statistical Tools & Environments: BASE SAS, SAS EG, SAS Studio, SAS EM, SAS/Macro, SAS/Graph (at UNIX and Windows environments), SQL, Python, R

SAS Procedures: Proc Sql, Proc Reg, Proc Glm, Proc Sort, Proc Freq, Proc Means, Proc Contents, Proc Tabulate, Proc Summary, Proc Plot, Proc Rank, Proc Risk, Proc Print, Proc Report, Proc Univariate

PROFESSIONAL EXPERIENCE

Senior Data Scientist

Confidential, MD

Responsibilities:

• Queried and mined large data sets, using SAS and SQL, to discover transaction patterns, examined financial data and filtered for targeted information using traditional as well as advanced analytic methodologies to proactively identify fraud trends, at Internal Revenue Services (IRS).
• Analyzed data using SAS and SQL to identify the taxpayers effected by the automated bot activity.
• Managed regularly the analysis of strategy performance, including false positive rates and recommended revisions to reduce fraud losses.
• Led the development and execution of various fraud metrics and algorithms for domestic and international fraud mitigation strategy, using SAS and SQL.
• Measured, monitored, and analyzed historical trends and external factors impacting the risk exposure.
• Led monthly and weekly meetings with client and other stakeholders to present and discuss strategies’ performance.
• Trained and mentored colleagues and junior analysts.

Senior Financial Analyst

Confidential, VA

Responsibilities:

• Evaluated existing regional and national collector commission strategy, and provided analytical support using SAS and SQL to reduce commission losses.
• Developed various of weekly, monthly and ad hoc reports using SAS and SQL, and utilized to drive decisions and measure success.
• Led several data investigations and ad-hoc analyses to identify specific issues within the strategy and presented the recommendations to senior management.

Senior Risk Analyst

Confidential, PA

Responsibilities:

• Analyzed existing Fraud Prevention strategies and advised developing two different models for peak season and non-peak season using FraudNet. Newly designed and calibrated models and improved algorithms resulted in a reduction of risky order manual review by 30% YoY and 21 % lower dollar losses.
• Lead the QVC Germany, France and Italy portfolios remotely to incorporate FraudNet in business operations. Provided consultation and training to 50-person business team to utilize FraudNet to mitigate fraud losses.
• Managed both internal and external stakeholders during the FraudNet upgrade, conducted testing for the algorithms before deployment and completed post-upgrade troubleshooting across the department.
• Researched value frauds and patterns using SAS and SQL, presented findings to senior level stakeholders and modified algorithms to prevent customer account compromises on a regular basis.
• Analyzed historical customer data using SAS and SQL, and projected the impact on revenue and charge off from QCard "credit limit decrease" strategy perspective.
• Employed complex analyses to identify correlations, estimates for losses, and probable loss amounts over varying horizons and management scenarios.

Credit Analyst

Confidential

Responsibilities:

• Functioned as a judgmental analyst and validated information required to determine the creditworthiness of a borrower prior to funding a new loan.
• Researched and validated customer information using research services such as LexisNexis and Clarity for fraud detection and loan underwriting.

Risk / Strategy Analyst

Confidential

Responsibilities:

• Evaluated the performance of existing BAU Student Credit Line Decrease strategy, by analyzing P&L of historical campaign, and identified opportunities to reduce credit losses on the Student Portfolio. Developed a decision tree (CHAID) using SAS, SQL and Angoss to target high-risk accounts based on expected year 2 NCL for 3,500 accounts and presented key findings to senior management for approval. Redesigned and calibrated new Student Credit Line Decrease strategy reduced credit losses by 42%.
• Provided analytical support using SAS and SQL to improve OMNI customer credit request strategy, which resulted in an improvement in the overall automation rate by about 25% and approximately 3,000 customer credit requests were auto decisioned per month. Performed post implementation validation of strategy in production and monitored continued performance on regular basis.
• Developed a robust authorization MIS report and automated the report for monthly production, using SAS.
• Performed several ad-hoc analyses, including waterfall reports, data investigations, etc. to identify and address specific issues within existing account management strategies.
• Performed quantitative and statistical analysis, using SAS and SQL on transactional data, to optimize credit policy to accounts with over-limit transaction or delinquency.

Pricing Analyst / Intern

Confidential

Responsibilities:

• Assessed the impact of the new internal risk score on existing pricing strategies by using data mining and proposed risk-based segmentations.
• Led monthly test and control meetings with senior management to discuss strategies’ performance.
• Analyzed large datasets by using SAS and SQL, and developed monthly MIS reporting for Late Fee and Over Limit Fee.
• Managed detailed analysis to minimize balance attrition impact from "risk based re-pricing" perspective and performed ad-hoc analyses, using SAS and SQL.

Marketing Analyst / Intern

Confidential

Responsibilities:

• Ranked physician level population by product utilization using SAS and SQL, and identified ‘top-decile’ regions in US for several brands.
• Analyzed performance of four brands’ marketing campaign by conducting PCP segmentation and sampling analysis and provided quantitative insights to senior management, using SAS and SQL.
• Compiled data from QCI (Quantitative Commercial Insight) brand managers for OptimAZ optimization project.
• Developed physician adherence scores to observe and analyze time trends of existing sales strategies.
• Served as a part of Corporate Operations Quality Initiative Department’s (COQI) internal exceptions database team and assisted in modifying exceptions databases for improving functionality.
• Customer Service call monitoring project: Gathered, trended and analyzed call data in order to analyze the root cause of service quality degradation by performing data mining using SPSS, SAS, SQL and Angoss software.
• Generated weekly reports for review by the companies’ senior management.

Graduate Research Assistant

Confidential

Responsibilities:

• Developed a web based survey using Persus survey program for CRM (Customer Relationship Management).
• Obtained and processed data from hotels, and performed linear regression modeling using SPSS, SAS and SQL.
• Reviewed literature and researched use of IT in Hospitality industry and presented in regional conferences.