Results-driven Software Engineer with expertise in JavaScript, Python, and data visualization. Proven ability to architect impactful features and deliver AI-driven solutions in full-stack environments.
Overview
7
7
years of professional experience
Work History
Software Engineer
Secunetics
Washington, DC
10.2021 - Current
Architected and delivered full-stack features for Gobo, a government-facing SaaS platform for network performance monitoring and public comment analysis, using a React / Python (Flask) / PostgreSQL stack.
Owned the end-to-end full-stack development of the "Comment Review" dashboard - a system that uses AI to categorize, score substantiveness, and cluster similar public comments - enabling users to review comments up to 10x faster than the legacy system.
Built reliable Python microservices for a service-oriented backend, rigorously applying test-driven development (TDD) to achieve and sustain 100% test coverage across all services.
Contributed dozens of reusable React components, pages, and navigational elements to a shared frontend library, standardizing the UI, reducing code duplication, and streamlining data fetching for the engineering team.
Integrated features into GitLab CI/CD pipelines across staging environments for safe, automated deployment.
Onsite Consultant at USPS
LMI
Washington, DC
11.2019 - 10.2021
Collaborated with USPS Revenue and Financial Accounting (RAFA) team to improve fraud detection, claims processing, and financial reporting systems.
Helped develop a decision tree model to detect fraudulent claim patterns, contributing to the uncovering of a $1M+ fraud scheme in Las Vegas.
Integrated the model into CICRS, the automated claims platform, helping block suspicious activity before payments were issued.
Enhanced CICRS with system-level workflow improvements aimed at increasing data integrity and auditability.
Produced actionable insights for leadership by cleaning and analyzing financial datasets and preparing ad hoc reports.
Senior Analyst (Data Visualization)
LMI
Tysons Corner, VA
12.2018 - 11.2019
Supported the Maintenance and Availability Data Warehouse (MADW™) project, ensuring accurate Tableau dashboard refreshes, and validating data consistency across DoD systems.
Developed a new interactive Tableau dashboard to expand MADW’s analytics suite, enhancing decision-making for maintenance and logistics teams.
Automated synthetic data generation using Python, creating statistically consistent mock datasets for secure client demonstrations.
Designed and deployed a contract vehicle dashboard enabling leadership to analyze trends in government project funding, leveraging dynamic filtering for granular insights.
Structured relational data models to support multi-level drill-downs, improving visibility into contract utilization and bid strategy.