Key Strengths

Demonstrated interest in AI/ML through multiple personal projects (AI-Vision-Detection, V.A.U.L.T, SmartRupee-AI, CollisionGuard-AI, Netflix-Content-Classification-and-Recommendation-System).
Experience with Python, Jupyter Notebook, and relevant libraries for data science tasks.
Exposure to various AI models including YOLOv8, CNN, and Transformer-based semantic models.
Practical application of AI in diverse domains like object detection, finance, and content recommendation.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate shows a strong inclination towards personal projects, indicating self-motivation and a proactive learning approach. The diversity of projects, from AI-powered finance trackers to collision detection systems, suggests an adaptable mindset. However, the lack of team-based projects or collaborative experience makes it difficult to fully assess cultural fit. The target role is 'Data Scientist', which aligns well with the candidate's project portfolio.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, and there are no psychometric test results or interview feedback.

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J Joshua Haniel

Data Scientist

https://www.opentalent.in/j-joshua-haniel

I'm a 20-year-old CSE student at SRM University, passionate about software development and problem-solving.

SNR AUTOMATIONS

ChennaiMember since June 12, 2026

https://www.opentalent.in/j-joshua-haniel

Top Skills

typescriptPL/pgSQLCSSHTMLJavaScriptJupyter NotebookPythonNixShellBatchfile

Skills

typescriptPL/pgSQLCSSHTMLJavaScriptJupyter NotebookPythonNixShellBatchfile

Experience

SNR AUTOMATIONS

Data Scientist

June 12, 2026 – Present

Projects

CollisionGuard-AI

March 21, 2026 – Present

CollisionGuard AI - Real-time collision detection and navigation guidance system using AI-powered object detection and depth estimation. Stay safe with intelligent obstacle awareness and actionable navigation recommendations.

View Project

Ai-life-copilot-HF26

March 9, 2026 – Present

Ai-life-copilot-HF26 — GitHub repository

View Project

Netflix-Content-Classification-and-Recommendation-System

August 20, 2025 – August 20, 2025

An AI-powered system that classifies Netflix titles (Movie vs. TV Show) and recommends similar content using both TF-IDF and Transformer-based semantic models. Built with Python, scikit-learn, Sentence Transformers, and Gradio for an interactive UI.

View Project

V.A.U.L.T

April 12, 2025 – April 25, 2025

V.A.U.L.T. is a fintech project featuring a CNN model for data processing, an API for financial data, and both web and mobile interfaces. It integrates secure and scalable technologies like Jupyter Notebook and TypeScript for enhanced user interaction and data analysis.

View Project

AI-Vision-Detection

March 27, 2025 – September 6, 2025

The AI-Vision-Detection project detects objects in uploaded images using a pre-trained YOLOv8 model and provides insightful visual outputs. Users upload images—typically via Google Colab—and the system processes them using OpenCV, Matplotlib, and NumPy to display detected objects with bounding boxes, alongside analytical visualizations like object.

View Project

Key Strengths

Demonstrated interest in AI/ML through multiple personal projects (AI-Vision-Detection, V.A.U.L.T, SmartRupee-AI, CollisionGuard-AI, Netflix-Content-Classification-and-Recommendation-System).
Experience with Python, Jupyter Notebook, and relevant libraries for data science tasks.
Exposure to various AI models including YOLOv8, CNN, and Transformer-based semantic models.
Practical application of AI in diverse domains like object detection, finance, and content recommendation.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, and there are no psychometric test results or interview feedback.