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andrewbantly/README.md

Software Engineer at SoBet

Languages

My Skills

Frameworks

My Skills

Infrastructure

My Skills

Passion Project

LeasePeek | Frontend Repository Backend Repository

Description: Engineering a data-driven app for large-scale property managers to forecast rent trends using analytics. Utilizing TypeScript, React, Chakra UI, Python, Django, Pandas, MongoDB, PostgreSQL, and REST APIs. Scripting unit and integration tests; leveraging Docker.

Past Projects

GroundBreakers Excavation | GitHub Repository

Description: Built a family business website with SEO and accessibility using JavaScript, React, Chakra UI, and Netlify. Integrated serverless email alerts, boosting visibility, inclusivity, and client engagement.

World Class Wines | GitHub Repository

Description: Programmed an interactive data visualization with JavaScript, React, D3.js, and Python, simplifying wine discovery by preferences, praised for user experience.

National Parks Explorer | GitHub Repository

Description: Co-developed a MERN stack app, enabling users to discover U.S. national parks and log visits, with features like REST APIs, JWT authentication, and CRUD operations.

Major League Baseball Pick'em | GitHub Repository

Description: Crafted a full-stack Node app using JavaScript, featuring real-time game odds, social interactions, and performance metrics, supported by relational databases.

Escape From Alcatraz | GitHub Repository

Description: Engineered an interactive game leveraging JavaScript for DOM manipulation, behavioral logic, and object detection, enhanced with intricate CSS styling.

Portfolio

andrewbantly.dev

Contact

andrewbantly@gmail.com

Pinned Loading

  1. leasepeek leasepeek Public

    Frontend: Building a data-driven web app for large-scale property managers to forecast rent trends using analytics. Utilizing TypeScript, React, Chakra UI, Python, Django, Pandas, MongoDB, PostgreS…

    TypeScript 2

  2. leasepeek-server leasepeek-server Public

    Backend: Building a data-driven web app for large-scale property managers to forecast rent trends using analytics. Utilizing TypeScript, React, Chakra UI, Python, Django, Pandas, MongoDB, PostgreSQ…

    Python 1