Implemented OOP-designed Python components with data structure application (hash maps, priority queues, graph-based dependency resolution) for a production pipeline processing 1,000+ inputs - built SQL-equivalent relational schemas and NoSQL vector storage (ChromaDB) on GCP (AWS-analogous); used AI tools for dev productivity (Claude Code, GitHub Copilot), maintained Git version control, and debugged complex system failures using systematic root-cause analysis
Software Engineer (Remote)
StayNova
06.2025 - 01.2026
Designed OOP-structured Python and TypeScript components with data structure implementation (spatial indexes, relational schemas, classification algorithms) - deployed SQL-equivalent and NoSQL database systems on Google Cloud (AWS-analogous); used AI tools for development productivity, maintained Git, debugged complex production failures systematically, and shipped to 200+ users with 95% satisfaction across the full SDLC
Full Stack Developer
African Development Group Columbia
09.2025 - 10.2025
Implemented OOP TypeScript components with NoSQL database systems (Firebase) on GCP (AWS-analogous) - applied data structure design for efficient queries, used AI tools for productivity, maintained Git, debugged production issues systematically, and drove a 70% measurable engagement increase through analytical problem-solving across the SDLC
Software Engineer (Remote)
Froglet Games
10.2025 - 01.2026
Implemented data structures and OOP algorithms in C# (Java-comparable) - debugged complex real-time system failures systematically, maintained Git, adapted rapidly to new APIs, and collaborated effectively with senior engineers across the full SDLC
Loan Approval AI Advisor, Columbia Applied ML, 2025-09-01, Implemented Python OOP components with data structure application (vector indexes, relational schemas, classification algorithms: Logistic Regression, Random Forest via scikit-learn)., Built SQL and NoSQL database systems (ChromaDB, PostgreSQL-style), deployed to cloud (AWS Lambda-analogous FastAPI), used AI development tools throughout, maintained Git, and debugged complex pipeline failures systematically.
Data Structures & Algorithm Suite, Columbia University - COMS 4701, 2024-09-01, Implemented foundational data structures and algorithms in Python - graph traversal (BFS/DFS with adjacency list + queue/stack), A
(priority queue + heuristic), UCS, CSP (constraint graphs), simulated annealing and genetic algorithms (optimization)., Applied systematic analytical problem-solving and used Git for version control throughout.
Air Pollution Data Processing Pipeline, Columbia University, 2023-09-01, Applied Python data structure and algorithm implementation to large-scale real-time data processing., Designed SQL-equivalent query structures on cloud infrastructure (AWS-analogous), debugged complex data pipeline failures systematically, and rapidly adapted to new REST API data sources.