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Billy B. Full-Stack, Cloud and Modern Frameworks

My name is Billy B. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Python, Golang, React, node.js, TypeScript, etc.. I hold a degree in . Some of the notable projects I’ve worked on include: Cenit Finance, Targeted Advertising System & API Built with AWS Cloud Environment, AI Community Matching Platform (React/Python). I am based in Jackson, United States. I've successfully completed 3 projects while developing at Softaims.

My passion is building solutions that are not only technically sound but also deliver an exceptional user experience (UX). I constantly advocate for user-centered design principles, ensuring that the final product is intuitive, accessible, and solves real user problems effectively. I bridge the gap between technical possibilities and the overall product vision.

Working within the Softaims team, I contribute by bringing a perspective that integrates business goals with technical constraints, resulting in solutions that are both practical and innovative. I have a strong track record of rapidly prototyping and iterating based on feedback to drive optimal solution fit.

I’m committed to contributing to a positive and collaborative team environment, sharing knowledge, and helping colleagues grow their skills, all while pushing the boundaries of what's possible in solution development.

Main technologies

  • Full-Stack, Cloud and Modern Frameworks

    2 years

  • Python

    1 Year

  • Golang

    1 Year

  • React

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Amazon

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Experience Highlights

Cenit Finance | Manage and transfer funds between your bank accounts

Securely manage and transfer funds between your linked accounts. Connect any banking account using Plaid, and securely transfer funds between connected accounts using Dwolla.

Targeted Advertising System & API Built with AWS Cloud Environment

Challenge Scalable system to process data, download web pages with access restrictions, and build groups of relevant users for campaigns The project was splitted into three phases: - Proof of Concept (PoC) – verify the idea that machine learning can be used for targeted advertising - Minimum viable product (MVP) – build the end-to-end data pipeline from processing user data to building user segments - Scalable system – make the solution scalable and connect it to the Client’s advertising platform via API.

AI Community Matching Platform (React/Python)

Built core features for an AI-powered virtual networking platform that drives community engagement by automating 1:1 and small-group matchmaking at scale. Designed and implemented smart matching algorithms, seamless scheduling flows, feedback collection tools, and analytics dashboards. Enabled branded communications and integrated video chat-all to create meaningful connections with minimal admin overhead.

Education

  • Sullivan University

    in

    2008-01-01-2008-01-01

Languages

  • English