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Zomato-Sentiment-Analysis
May 4, 2026 – Present
Zomato-Sentiment-Analysis — GitHub repository
View ProjectData-Difficulty-Index-DDI-
April 13, 2026 – Present
Data-Difficulty-Index-DDI- — GitHub repository
View ProjectKafka-Spark-Redshift-Streaming-Data-Ingestion-Project
January 25, 2025 – January 25, 2025
This project is a real-time data pipeline designed for ingesting, processing, and storing telecom call records. It integrates Apache Kafka, Apache Spark Streaming, and AWS Redshift to handle large volumes of streaming data in near real-time. The pipeline is containerized with Docker Compose, enabling easy deployment, scalability, and modularity.
View ProjectProcess-and-Ingest-only-quality-movies-in-Redshift-Dara-Warehouse
January 24, 2025 – January 24, 2025
This repository contains a production-grade ETL (Extract, Transform, Load) pipeline built with AWS Glue and Amazon Redshift. The pipeline processes a raw IMDb movie dataset stored in Amazon S3, applies data quality validation, dynamically routes data based on validation results, and loads it into Amazon Redshift for advanced analytic
View ProjectHeadline_Generation_and_Summarization_of_News_Articles_with_T5_and_XSum_Dataset
January 23, 2025 – January 27, 2025
This project implements a headline summarization pipeline using the T5 transformer model fine-tuned on the XSum dataset. It provides a user-friendly interface using Gradio to generate concise summaries for long headlines or paragraphs. The project showcases end-to-end machine learning capabilities, from preprocessing and fine-tuning to deployment
View ProjectCSforAll_coding_assignments
January 23, 2025 – January 30, 2025
CSforAll_coding_assignments — GitHub repository
View ProjectRewardsPortal
April 27, 2024 – January 12, 2025
The Rewards Portal is a user-friendly Q&A platform, inspired by the concept of StackOverflow, where users can ask questions, view answers, and manage their profiles. It provides a seamless experience for managing personal information, posting queries, and rewarding user engagement. This project is built using Python, Flask, Bootstrap, and JSON.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards data science and machine learning, aligning well with a Data Scientist role. The diversity of projects, from real-time data ingestion to NLP and ETL, suggests adaptability and a broad interest in the field. However, the lack of team-based projects or explicit collaboration details makes it difficult to fully assess cultural fit beyond technical alignment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate an ability to work on complex technical challenges independently.