Data Operations TeamReduced Snowflake operation cost by 50%, saving $1.2 million annuallyDesigned and developed data pipelines on Snowflake processing 600+ million records dailyOptimized performance of pipelines, reducing query time by orders of magnitudeDesigned and led migration of data platform to use dbt, streamlining developmentStreamlined Snowflake account management utilizing CDKTF (Terraform)

Real Time Machine Learning Fraud Decisioning Platform Real-time, highly scalable, low latency solution processing 100+ million transactions per dayComplete rebuild of existing service to leverage Spark clusterLeverages historical and profile matches across dozens of fields while providing low-latency responsesAutomated extracts for Decision Science team; Quick to deploy new modelsUtilizes Machine Learning frameworks (XGBoost, Keras/Tensorflow, others)Derived Data and Service for ML ModelsReal-time service providing derived data for transactionsRetrieves hundreds of fields across billions of records and returns a response in ~4-6 msReal-time ingestion for all transaction dataSpark computations that recomputes profile, historical, fraud-to-gross, and ratios model variablesDynamic config; Recompute nightly and on demand for entire historyRequired extensive optimizations due to high volume and fluidity of data and small size of clusterBig Data Platform SupportDeveloped POCs for adding ML frameworks to existing productsXGBoost, Keras/Tensorflow, deeplearning4j, In-house gradient boosting model, log regressionsDeveloped POCs for modeling workflows leveraging SparkInstrumental in transforming the way the Decision Science team leverages dataProvided support for any critical issuesAutomated Machine Learning Model Generation for Fraud DetectionGenerated multiple model types: rule-based genetic algorithm, neural networks, svm, log. regressionDecreased run-time from several months to a couple of days per modelMachine Learning models provided a 20-50% reduction in review ratesEmployee Recognition Award for work on the automated machine learning tool

BAM Redesign 1B, Blue Cross Blue ShieldDesigned and implemented a tag library that significantly decreased development time and code required, while increasing maintenance and usability for a content-based applicationBecame SME for content system across multiple releasesDeveloped multiple portlets using Spring 3Extended a pdf solution to dynamically create pdf files based on htmlBuilt a custom automation tool to merge personalization rules for Portal across multiple releases

GCAS CIM Mobile WorkforceSenior Specialist-Applications DeveloperDesigned and implemented a new web services framework for JAX-WS- Reduction of web service code by over 50% to 90% per interfaceConverted 14 interfaces (60 operations) from JAX-RPC to JAX-WSCreated documentation for adding future web services to the frameworkCo-implemented transaction history using JavaScript, JSP, and HTML5 localStorageSaved the company $30,000 plus $6,000 in annual renewal fees by providing an alternative solution in dynamic pdf creation.GCAS Uverse Mobility for GSLSenior IT AnalystGSL provides a Web Service framework to expose GCAS functionality for mobile devicesKey contributor to discussions on design and implementation of GSL Led discussions and reviews for 4 interfaces (14 operations) as web servicesDesigned and developed 4 web servicesInstructor for Java 2 Training during Q4 of 2010GCAS SE TAIT AnalystAT&T 2010 Key Contributor Award RecipientConverted GCAS from Java 1.4 to Java 1.6Designed and developed 2 interfaces (one web service, and one JMS)Designed and developed a portlet using JSP, Java, JavaScript, and Struts Portlet architecture in WebSphereInstrumental in resolving a production defect on another interfaceTemporarily assumed Application Architect LeadMentored 2 resources on GCASAssistant Instructor on Java 1 Training during Q3 2010GCAS LS DCOEIT AnalystLed discussions and reviews on 7 batch (ftp) interfaces and 2 web service interfacesDesigned and developed 2 web services (12 operations)Designed and developed a SAX parser Assumed Application Architect Lead role during late development phaseAttended UNIX and Java Developer forums.