Anurag Kumar Singh

Data Scientist and GenAI enthusiast with a strong focus on problem solving, data understanding, and building intelligent solutions. Experienced in analyzing real world data using statistics, machine learning, and NLP to uncover patterns and support decision making. Skilled at transforming messy and unstructured data into actionable insights and scalable ML and GenAI systems with a mindset focused on clarity, innovation, and real world impact.

Completion of Introduction of AIML

1. Road Safety & Crash Intelligence System (Capstone Project)
Domain: Machine Learning & Analytics
Built a real-time, multi-model system on police crash data to identify high-risk zones, injury severity, and accident patterns using classification, clustering, and EDA.

2. Financial Stress Index & Dynamic Credit Cost Prediction System
Domain: Regression & FinTech Analytics
Developed regression models with time-based validation to predict financial stress levels and dynamic credit cost trends for business decision-making.

3. Online Retail Customer Segmentation & Recommendation System
Domain: Clustering & Recommendation Systems
Segmented customers using K-Means and built a recommendation logic to suggest top-selling products and improve marketing effectiveness.

4. Open World Resume Intelligence System (Deployed)
Domain: Generative AI & NLP
Designed and deployed a GenAI-powered resume analysis system using semantic embeddings to generate recruiter and candidate-focused insights.

5. NeuroRoute — Neural NLP Issue Routing System
Domain: Deep Learning & NLP
Built a Bi-LSTM-based neural text classification system to automatically route long, unstructured issues to the correct business domains.

6. Mental Health Text Analysis & Risk Classification System
Domain: Natural Language Processing
Analyzed and classified mental-health-related text using TF-IDF, machine learning models, and imbalance handling techniques.

7. Food Quality Inspection & Shelf-Life Risk Prediction System
Domain: Computer Vision
Developed an image-based system to assess food quality and predict shelf-life risk for quality inspection use cases.

8. Prompt-Driven Customer Complaint & Incident Intelligence System
Domain: Generative AI & NLP
Built a prompt-engineered system to extract structured insights and trends from large-scale customer complaints and incident narratives.

9. Multi-Modal Knowledge Assistant using RAG
Domain: Generative AI (RAG)
Implemented a retrieval-augmented generation system combining embeddings and vector search for context-aware question answering.

10. Business Intelligence Dashboards (Tableau & Power BI)
Domain: Data Visualization
Created interactive dashboards using Tableau (advanced) and Power BI (basic) to analyze sales, customer behavior, and operational metrics.