👋 Hey there! I'm Tarang Kishor I'm a passionate Python programmer and AI/ML enthusiast, and I’ve been in love with programming ever since. 💻
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Ethara.AI
Data Scientist
June 21, 2026 – Present
Leaderboard-API
March 15, 2026 – Present
A production-grade **real-time leaderboard REST API** built with FastAPI — powered by a **skip list data structure implemented from scratch**, with no Redis or external sorted-set library.
View ProjectSmart-Incident-Prevention-Agent
January 31, 2026 – Present
A multi-agent AI system that transforms enterprise incident management by automating the detection, analysis, and response workflow while maintaining human oversight for critical decisions. Built with IBM watsonx Orchestrate to demonstrate coordinated agent collaboration with explainable AI principles.
View ProjectReal-Estate-Investment-Advisor
December 3, 2025 – December 12, 2025
Real Estate Investment Advisor is a full-stack, ML-driven Flask app that helps users evaluate Indian property listings. Trained on 250K+ records, it combines an XGBoost classifier to label properties as “Good Investment” or “Not Recommended” and an XGBoost regressor to forecast 5‐year price appreciation.
View ProjectAerial-Object-Classification-and-Detection
November 27, 2025 – November 27, 2025
This repository implements a comprehensive deep learning solution for classifying and detecting aerial objects (Birds vs Drones) using multiple approaches.
View ProjectAI-Powered-EMI-Risk-Assessment
November 12, 2025 – November 12, 2025
This comprehensive financial risk assessment platform integrates machine learning models with MLflow experiment tracking to create an interactive solution for EMI prediction.
View ProjectCSAT-Prediction-using-Deep-Learning
October 15, 2025 – October 21, 2025
This project focuses on predicting Customer Satisfaction (CSAT) scores using Deep Learning Artificial Neural Networks (ANN). By leveraging advanced neural network models, we aim to accurately forecast CSAT scores based on a myriad of interaction-related features, providing actionable insights for service improvement.
View ProjectE-Commerce-Delivery-Time-Prediction
October 5, 2025 – October 5, 2025
This project aims to predict delivery times for e-commerce orders based on various factors such as product size, distance, traffic conditions, and shipping method. Using the provided dataset, we will preprocess, analyze, and build regression models to accurately estimate delivery times.
View ProjectBasic-Personal-Expense-Tracker
October 3, 2025 – October 3, 2025
A basic personal Expense Tracker
View ProjectCultural Fit Analysis
The candidate's portfolio showcases a strong inclination towards personal projects, demonstrating initiative and a passion for applying data science and machine learning to various real-world problems. The diversity of projects, from real-time APIs to financial risk assessment and deep learning for CSAT prediction, indicates a broad interest and adaptability. The 'Smart-Incident-Prevention-Agent' project, utilizing IBM watsonx Orchestrate, suggests an interest in cutting-edge AI platforms and collaborative agent systems, which could be a good fit for innovative teams. However, the lack of team-based project descriptions or explicit collaboration experience limits a deeper cultural fit assessment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and hands-on approach to problem-solving. The 'Smart-Incident-Prevention-Agent' project suggests an interest in multi-agent systems and explainable AI, which aligns with advanced operational thinking. However, without specific soft skill assessments or interview data, a comprehensive evaluation of soft skills and operational fit is limited.