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MSc Data Science @ PSG TECH
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
stpm-anomaly-detection
April 21, 2026 – Present
stpm-anomaly-detection — GitHub repository
View ProjectVAG-Diagnostic-Inference-Engine
April 16, 2026 – Present
A rule-based AI Expert System for VW Polo 1.2 TSI diagnostics, featuring a symbolic knowledge base and an explainable inference engine.
View ProjectIndian-Railways-Spatial-Analytics
April 14, 2026 – Present
Indian-Railways-Spatial-Analytics — GitHub repository
View Projecttwitter-sentiment-mapreduce
April 14, 2026 – Present
twitter-sentiment-mapreduce — GitHub repository
View Projectstartup-validator
April 11, 2026 – Present
A production-grade, event-driven microservices platform for startup idea validation. Built with FastAPI, Kafka, PostgreSQL, MongoDB, and Llama 3.3 Agentic AI. Deployed on AWS EC2.
View Projectcredit-risk-system
December 23, 2025 – Present
End-to-end Enterprise Credit Risk System using Random Forest (94.16% Accuracy), Flask, PostgreSQL, and Streamlit. Features real-time loan decisioning, NPA analytics, and a causal synthetic data pipeline.
View Projectimagify-image-generator
November 26, 2025 – Present
imagify-image-generator — GitHub repository
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a strong interest in data science, AI, and machine learning, aligning well with a Data Scientist role. The diversity of projects, from sentiment analysis to credit risk systems and AI expert systems, suggests a broad curiosity and willingness to explore different domains. The use of modern technologies like FastAPI, Kafka, and AWS indicates an awareness of industry best practices for deploying data-intensive applications. However, without information on team-based projects or contributions to open source, it's 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 diverse technical challenges, but there is no information on collaboration, communication, or problem-solving in a team context.