Edwin R. Email & Phone Number

Chapel Hill, NC, US

Toronto, Ontario, CA

Santa Clara, CA, US

• Transaction monitoring
• Effectively implemented a new AML transaction monitoring system with a team in atime-frame condensed to 6 months by leading data and rule mapping exercises
• Modernized our transaction monitoring rules while simultaneously integrating new customers,accounts, and transactional data from a bank acquisition
• Enhanced fraud monitoring rules through the use of developed emulations
• Design and develop AML monitoring tools, programs and models using a risk-based approach
• Evaluate the effectiveness of existing AML modeling tools, programs and models and tune them as needed using a risk-based approach

New York, NY, US

• Responsible for helping to develop and validate leading edge AML models for transaction monitoring, name matching, watch-list monitoring, customer risk scoring and providing input to the framework for AML model.
• As an SME for AML model development and validation, provide day-to-day direction to the team,acting as the main go to person and providing informal coaching to teams to build this offeringto clients within Banking and.
• Provide consulting and timely advice to clients on accurate frame work for AML modeldevelopment and guide clients on validating existing AML models.
• Test, review and validate AML models
• Assist technical writers with model documentation, following the AML and EnterpriseModeling Governance standards
• State key assumptions, including quantitative, qualitative and expert judgment, logic andconceptual soundness; conduct various tests.

Cary, NC, US

• Work as a senior AML analytics consultant in SAS’s Fraud & Compliance Professional Services division where my role is to help develop and apply SAS’s AML solution and optimization business (monitoring, segmentation.
• Assist customers in developing robust AML customer / account segmentation models that allow for effective risk-based transaction monitoring scenario threshold setting.
• Develop and apply anomaly detection scenario to identify customer deviations from their historical activity and respective peer groups
• Perform ongoing transaction monitoring scenario tuning exercises aimed at optimizing the scenarios’ effectiveness and efficiency (i.e. distribution analysis, initial threshold setting, below-the-line testing.
• Develop robust and effective statistical predictive models used to enhance the current transaction monitoring scenarios (i.e. customer risk rating).
• Assist customers in meeting the regulatory expectations with regards to model validation (specifically OCC 2011-12).

Cary, NC, US

• Work as a data scientist in SAS’s Research and Development division where my role is to help develop and apply SAS’s AML solution and optimization business (monitoring, segmentation, scenario tuning, and model.
• Design, develop, and debug software for new and existing products in accordance with designated development practices and timelines.
• Analyze both business and system requirements working directly with development, testing, deployment, usability, and documentation teams, as well as customers, delivery teams, product management, and others.
• Analyze data, applying analytics, building analytical models, researching and evaluating new algorithms and technologies
• Present findings and solutions across various domains such as compliance, fraud, and security intelligence in any number of industries
• Interact and advise delivery teams around the globe, while harvesting information to enhance solutions.

Cary, NC, US

• Work as a consultant in SAS’s Professional Financial Services division where my role is to help develop and apply SAS’s AML segmentation, scenario tuning, and model validation advisory business.
• Assist SAS customers in developing robust AML customer / account segmentation models that allow for effective risk-based transaction monitoring scenario threshold setting.
• Perform ongoing transaction monitoring scenario tuning exercises aimed at optimizing the scenarios’ effectiveness and efficiency (i.e. distribution analysis, initial threshold setting, below-the-line testing.
• Develop robust and effective statistical predictive models used to enhance the current transaction monitoring scenarios (i.e. customer risk rating).
• Assist SAS customers and non-customers in meeting the regulatory expectations with regards to model validation (specifically OCC 2011-12).
• Assist customers with determining the most appropriate SAS platform scenarios based on their unique AML risk profile, product offerings, customer / account base, and experienced transactional activity.

New York, New York, US

• Perform ongoing transaction monitoring scenario tuning exercises aimed at optimizing the scenarios’ effectiveness and efficiency (i.e. distribution analysis, below-the-line testing, above-the-line testing, etc.).
• Develop robust and effective statistical predictive models used to enhance the current transaction monitoring scenarios.
• Applied statistical methods to organize, analyze, and interpret data related to AML monitoring scenarios and thresholds across different lines of business.
• Reduced the analysts’ workload by roughly 50% during the optimization process by combining similar segments, thus producing smaller representative sample sizes.
• Identified areas for continual improvement with the optimization statistician team and analysts, resulting in several data lists for targeted research on customers with specific characteristics.
• Provided written explanations of approach and analyses to support the conclusions and observations for sensitivity analysis.

New York, New York, US

• Developed scatterplots and bar charts to assist in optimizing Mantas scenarios and visualizing thresholds.
• Created a fuzzy matching program with a scoring method for comparing text fields that reduced the number of monthly alerts by roughly 350.
• Provided ad hoc data mining support to AML Operations for critical decisions.
• Developed partnership with IT group to provide for more efficient solutions to data, system, and application issues by noting areas of improvement such as data accuracy and integrity.

• Analyzed and evaluated medical claims data to reduce errors and increase accuracy in support of MEDai’s predictive modeling tool targeted at health plans.
• Performed high level data analysis and project management of production processes for large scale Oracle predictive modeling databases
• Tested, tracked, and monitored data for quality, integrity, and trend analysis by using SQL and DBA-developed tools.

• Responsible for data preparation and mapping of client data
• Loaded client data into Oracle tables using DBA-developed tools
• Created ETGs (Episode Treatment Groups) for use in predictive modeling
• Assisted with web technical QA of client data

Charleston, SC, US

• Coordinated and managed the loading of health carrier data into the Benefitfocus.com application (Bluesenroll.com).
• Responsible for updating and reconciling health carrier data
• Communicated issues and developed a problem resolution strategy to ensure timely and accurate data loading.
• Utilized Oracle Database processing tools to retrieve and verify information pertaining to carrier loads

Wilsonville, OR, US

• Updated Nucleus RTOS (Real Time Operating System) product line for tool/processor/product updates using source code, tools, and debuggers.
• Tested custom integration software (compiler/debugger application)
• Developed additional products, such as Compact Flash, from existing source
• Released timely product updates, which facilitated increased quarterly sales.

Masters Of Science, Data Mining

Bachelors, Computer Science

Minor, Communications

Education record