Skills

Technologies grouped by project and role context.

Skills In Context

Technologies are listed with the projects and roles where they were used. Entries below summarize implementation context and workflow usage.

Splitify

Project Context: playlist clustering and API behavior

Splitify combines Python-based clustering logic with API and client workflow work. The implementation emphasizes playlist grouping behavior and response handling for larger inputs.

Python JavaScript K-Means Clustering API Design Concurrency (Threads)

Slug Events

Project Context: full-stack delivery and deployment workflow

Slug Events involved full-stack delivery across Flask and Next.js with deployment on GCP. The workflow included CI/CD usage, sprint coordination, and routine release tasks.

Flask Next.js Google Cloud Platform GitHub Actions CI/CD Agile / Scrum Jira

Google Summer of Code at mitmproxy

Experience Context: open-source HAR import/export implementation

This work centered on implementing and validating HAR import/export behavior in an open-source codebase. It included handling edge cases, writing automated tests, and documenting behavior for contributors. The project CI required 100% code coverage, so tests were written to cover all code paths before merge.

Python Data Transformation Pytest 100% Code Coverage CI/CD Technical Documentation

AppCensus Internship

Experience Context: mobile app dataset analysis and tooling support

The internship combined mobile app dataset analysis with internal tooling support. Work included improving extraction outputs, analyzing datasets from 200+ apps, and making results easier for teammates to review through an internal React/Flask tool.

Data Analysis React Flask UI Improvements Mobile App Dataset Work

Good Research

Experience Context: ML pipelines and operational workflows

This role connected model development to operational workflows. Work included NLP pipelines on AWS Lambda, PyTorch model tasks, MLflow-based tracking, and internal tool development to support repeatable research and analysis workflows.

Python AWS Lambda PyTorch Gensim NLP (LDA) MLflow Data Pipelines Full-Stack Development

CCDC Competition

Experience Context: defensive operations and incident response

CCDC work emphasized triage, service uptime, and coordination during timed defensive scenarios. It required balancing fast response with reliable system changes.

Incident Response System Hardening Service Reliability Team Coordination Prioritization