Rome wasnt built in a day
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
HireFilter
May 21, 2026 – Present
Automated Resume Screening Tool that compares candidate resumes against a given job description and scores candidates based on relevance and provide justification
View Projectask-my-doc-rag
April 20, 2026 – Present
A modular Retrieval-Augmented Generation (RAG) application for domain-specific question answering over custom documents. Implements document ingestion, chunking, and semantic retrieval using Chroma, combined with LLM-based answer generation. Designed for extensibility toward hybrid retrieval and reranking.
View ProjectPushUp.AI
April 7, 2026 – Present
A real-time push-up counter using OpenCV and MediaPipe that detects human pose from webcam input, calculates elbow angles, and accurately tracks repetitions with live visual feedback.
View ProjectFraudLens-Agentic-AI-Fraud-Detection-Platform
April 6, 2026 – Present
Real-time fraud detection system built with Apache Kafka, Amazon S3, and ML on Databricks. Includes an agentic AI layer powered by an LLM for reasoning, explanations, and automated decision-making.
View ProjectLLM-Based-Mathematical-Reasoning-Evaluation-Optimization-System
March 30, 2026 – Present
A production-style AI system that evaluates and improves LLM reasoning performance using prompt engineering (SCoT) and LoRA fine-tuning, with automated benchmarking, error analysis, and interactive visualization.
View ProjectCredit-Card-Strategy-Analysis
March 18, 2026 – Present
Credit card strategy analysis using Python & Power BI to identify customer segments and recommend data-driven financial products.
View ProjectTwitter-Sentiment-Analysis
March 18, 2026 – Present
Modular NLP pipeline for Twitter sentiment analysis with feature engineering comparison and structured evaluation.
View ProjectCropGuard-GAN-CNN
February 11, 2026 – Present
GAN-enhanced CNN pipeline for crop disease detection with targeted data balancing to improve minority class performance.
View ProjectCultural Fit Analysis
The candidate demonstrates a strong passion for AI/ML through numerous personal projects, many of which align directly with the 'Data Scientist' target role. The breadth of projects (NLP, CV, RAG, fraud detection, mathematical reasoning) indicates a versatile individual eager to learn and apply diverse technologies. This aligns well with a culture that values innovation and continuous learning. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration and broader cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-driven individual capable of tackling complex technical challenges. The diversity of projects suggests adaptability and a willingness to explore different domains within AI/ML. However, without specific assessment data on communication, logical reasoning, or teamwork, it is difficult to fully assess soft skills and operational fit.