Software engineering, building software for retail products.• Built an automated shopper tool that increases purchasing of high profit SKUs by 1500%, increasing the average profit margin from 10% to 31.25% a week, over a 3 month evaluation, in a highly regulated industry• Helped the business owner to understand the greatest lift could be resale to competitors at over 100% MSRP

Software engineering, building software for retail products.• Contributed to software, that uses data science to estimate similar or same cars, that increased sales by many millions in a year timeframe• Working on customer prioritization of sales leads by phone, web leads, and subsequent follow-ups; poised to add multi-millions in overall revenue• Creating a near real time eventing feed of new features, to a feature store to increase the 0-24 hour profile of viable customers by as much as 30%• Updating the signature of a MLOps pipeline from a stale process, to a near daily, retrained model• Actively merging the best skills of a software engineer and a machine learning engineer into one super user• Creating an interaction model between data science, machine learning, and served models. This pattern grossly outways most "in-play" or open source ML Ops pipelines in existence.

Software engineering to integrate with a payments processor, Walmart in-store, and modernized Auto Pay.• Help design cost effective micro service architecture that is self-healing, ephemeral, and fast.• Outspoken proponent of shifting the "lift & shift" management style of cloud infrastructure to using well managed offerings from cloud providers, to help shift talented individual to more meaningful work. • Created Spark jobs to process several hundreds of thousands of payments in fast batches, reducing infrastructure costs to as little as $14• Supporting several core features that keep one of our most critical work functions up and operational.• Closely integrated with well managed enterprise support teams to personally contribute back to more robust & secure enterprise solutions to all software engineers through our cloud engineering and our infrastructure as a service teams.• Working with cloud engineering support teams to understand the complete networking and communication model of the infrastructure we decided to support on our Payments modernization products.• Outspoken proponent of solutions that are cheaper to license, with the same corporate security support, in lower support cost to leadership.

Software engineering to build a feature rich user interface with dynamically respond to user inputs to: sorts, filters, time caps, scrolls, and resize seamlessly on desktop or mobile.• Built new content with accessibility integration in mind. Content dynamically changes on an underlying grid to best fit any device the user interface is opened upon.• Built user interface in Angular 5 though Angular 7 to offer fast rendering, dynamic in browser processing of content, on lightweight single screen components.• Recreated images in modern browsers, with rare and antiquated data formats such as TIFF, and saved to a more modern, lossless image compression type of PNG.• Built a robust Java orchestration layer to handle sessions across clustered instances, customer permissions, enterprise security requirements and OAuth, and to separate a direct connection from end-users to the underlying APIs.• Supported two enterprise grade Java APIs to handle requests to get list of documents from an Elastic Search, and turn documents into byte arrays for consumption by the orchestration layer, and most clients accessing records or images.

Software engineering to build a robust, resilient, durable solutions that leverage enterprise standard CICD pipelines, to automate building, restoration, backups, and multi-site availability• Built a completely self-service onboarding system, to one of the largest credit card companies, to one of our largest Elastic Stacks. The stack reduces hardware needs, moves inbound log processing from a server-side pull, to completely client side push, making it completely self-service.• Publishing learnings of Java virtual machine theory, effective heap vs stack memory utilization and control, and minimizing hardware while maximizing effective usage of exceptionally large clusters.• Building cross-site replication, using Kafka, to offer replication across numerous physical regions, to ensure as close to 100% uptime as possible.• Integrating numerous tools into one visual, that captures the best of numerous monitoring solutions, to offer a collection of the best available options into one tool. The vision is to go from a global view, to drill down to the class and kernel level, to then find issues across a stack of machines.• Other value adds include integrating micro-services from third party vendors, to add business facing data where applicable, and adding machine learning to drop incident response time to less than 5 minutes.

Data analyst role on a bank fraud innovation team in recognition of higher level contributions to the team. Create dynamic fraud solutions on the fly to combat account takeover fraud and counterfeit debit fraud. Built new research tools and reporting to optimize staffing for several investigations teams. • Applied data engineering expertise to manage a 3 petabyte size data lake utilizing AWS EMR, to create one of our first PrestoDB implementations, to connect numerous disparate systems into one main querying engine, dramatically reducing the ETL effort during our shift to the cloud• Developed an algorithm with automated quality check logic which will improve matching of debit card fraud to authorizations from 90% to 95% and cut error rates from 19% to < 1%• Proactively self-taught in AWS and became team expert; co-created training and tools and coached business analysts enabling them to be self-sufficient in AWS tools in only 10 minutes• Selected as team expert to work with the Information Security & Risk Management team to create usable AWS security models across Capital One Bank• Used AWS products to cut wait time for customer queries from 30 minutes to 2 second, cutting costs 95%• Created a case management system for investigators built a web application using python; enabled responses within 2 seconds vs 30 minutes • Created an automated, fraud rule suite using data science skills that targeted all high risk populations and automatically decline high risk activities• Applied data engineering expertise to merge disparate data sets, using a parallel architecture to tag potential fraud using a single product to save cost of more expensive systems• Recognized by leadership for ability to develop and implement end-to-end solutions within incredibly short timeframes; dramatically improve efficiency and reduce risk in time-sensitive fraud environments

Conducted risk analyses, developed and implemented data management standards and improved controls for reviews by data consumers, data engineers, and information security auditors. Provided data and operational analysis for the risk analysis team.• Produced a reporting logic that captured 98% of potential losses to an account takeover ring, reducing potential monthly losses from $4M to < $25k• Created SQL based reporting and matching logic that improved 0-5 day fraud detection by >300%; real time process added over 30% lift in the first 14 days in a highly time-critical environment• Designed an E-Commerce, card not present fraud, identification system that has uncovered over 2000 compromised leads in 3 years with a > 95% success rate

• Managing a team of 5 in effective sales, upselling, and product value and presentations.