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Assessing your cultural and operational fit
shell-from-scratch-python
October 28, 2025 – October 31, 2025
shell-from-scratch-python — GitHub repository
View ProjectFrontendX-Backend
June 8, 2025 – June 8, 2025
A FastAPI backend that benchmarks website performance using Google PageSpeed Insights and provides AI-powered optimization tips via Groq LLM. Features endpoints for analysis, interactive AI chat, and full Lighthouse report downloads. Dockerized for easy deployment. Built for the FrontendX hackathon.
View ProjectIngredients-Analyzer-Advisior
June 8, 2025 – June 18, 2025
Ingredients-Analyzer-Advisior — GitHub repository
View ProjectMultilingual-Note-Taking-Agent
April 20, 2025 – April 22, 2025
An AI-powered assistant that transcribes multilingual meeting recordings, summarizes key discussions, extracts action items, enables chat-based Q&A, and supports keyword search — all through an intuitive Streamlit interface. Built using FastAPI, AssemblyAI, Groq API, and LangChain for the HOLON x KBI Hackathon 2025.
View ProjectBlog-Writer-Agent
April 16, 2025 – June 8, 2025
An autonomous content generation system built with Python and CrewAI that employs multiple specialized agents to research, write, and optimize blog posts. Powered by Google's Gemini LLM and real-time data APIs.
View ProjectLegal-AI-Chatbot
April 13, 2025 – June 8, 2025
An AI-powered assistant that transcribes multilingual meeting recordings, summarizes key discussions, extracts action items, enables chat-based Q&A, and supports keyword search — all through an intuitive Streamlit interface. Built using FastAPI, AssemblyAI, Groq API, and LangChain for the HOLON x KBI Hackathon 2025.
View ProjectYT-Chrome-Plugin-Frontend
November 15, 2024 – December 20, 2024
A powerful tool for content creators and analysts to gain insights from YouTube video comments. This extension seamlessly integrates sentiment analysis and advanced visualization features directly in your browser.
View ProjectComment-Sentiment-Analysis
October 27, 2024 – November 26, 2024
A sophisticated sentiment analysis project that classifies YouTube comments into positive, neutral, or negative sentiments using advanced machine learning techniques. This production-ready solution combines LightGBM for high-performance sentiment classification with modern MLOps practices.
View ProjectCultural Fit Analysis
The candidate demonstrates a strong interest in AI/ML and data science, aligning well with a Data Scientist role. The diverse range of personal projects, including hackathon participation, indicates a self-starter mentality and a passion for continuous learning and application of new technologies. The projects span various domains (sentiment analysis, content generation, performance benchmarking), suggesting adaptability and a broad technical curiosity. However, the lack of team-based or open-source contributions makes it difficult to assess collaborative cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and innovative approach to problem-solving, particularly in developing AI-powered tools. The focus on hackathon projects suggests an ability to work under pressure and deliver functional prototypes. However, without psychometric test results or interview data, specific soft skills like teamwork, stress handling, or communication clarity in a professional setting cannot be fully assessed.