Confidential, Raleigh, NC
- Built a data warehouse in Azure SQL Server that allowed stakeholder to get the data they needed to drive their business.
- Used SSIS to import data, Azure SQL Server to store it, Tableau to analyze it and SSRS to present it. Process automation cut manhours, eliminated human error and made the process repeatable, scalable and self - documenting.
- Managed permissions for teammates in Azure DevOps, which reduced security risks.
- Used infrastructure as Code (IaC) with Azure Resource Manager (ARM) templates to ensure application had just enough infrastructure to meet SLA. This cut project lead time by 90%
- Created an Azure DevOps Git repository and branching strategy. Implemented policies to enforce branching strategy, which ensured the source code would always build without error and pass unit tests.
- Automated Builds in Azure DevOps, which facilitated more efficient and productive developer collaboration.
- Created a DevOps pipeline that promoted application through Dev, SIT, UAT and Prod Environments, which automated testing, approval and release saving hundreds on manhours, cut lead times by over 50%, and reduced the risk of human error.
- Created predictive models in Python using linear regression, logistical regression and K Nearest Neighbor to determine which populations met ROI hurdles. Cut training costs by 35%.
- Served as scrum master, led ceremonies, created Features, User Stories, Tasks and Defects.
- Wrote, revised and gained approval for Business Requirements documents. Cut lead times from months to weeks.
- Identified sources for Mortgage, Checking, Credit Card, and Insurance data. Including data sourcing with requirement gathering removed ambiguity, eliminated rework and cut development time by 50%.
- Wrote, revised and gained approval for Data Requirements. Changed Data Requirement format to include more detail, leave less room for error and facilitate automated testing. Automated testing improved quality and cut man hours by 75%.
- Wrote, revised and reviewed SAS programs to extract campaign data. Fluency with SAS ensured program pulled right data from right places and cut time to revise and test code from weeks to days.
- Wrote, revised and reviewed PowerShell scripts to verify data files met requirements. Automated testing cut testing time and cost by an order of magnitude.
- Grew Countrywide’s Hard Money (Low LTV/Low Credit Score) Mortgage Acquisition program from inception to $80,000,000/month. Securitized over $1,250,000,000 making Countrywide’s Hard Money Desk the largest in the industry.
- Created Countrywide’s OLTP Database for whole loan and securitization. Built SSIS packages to import data and data warehouse for reporting and analysis. When Confidential acquired Countrywide, B of A adopted this system for use throughout all of Confidential . It is still in serve today.
- Used logistical regression to create prepayment, default, securitization and pricing models and credit risk scorecards.