Sr. Research Scientist at NielsenIQ
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NielsenIQ
Data Scientist
June 16, 2026 – Present
GenAI_Hands_On
August 24, 2025 – August 29, 2025
This repository contains hands-on exercises and demo notebooks for a workshop on Generative AI in Industry. Participants will explore both Generative AI and Agentic AI through practical, domain-focused use cases.
View ProjectDA_Lab
July 21, 2025 – July 22, 2025
Domain Adaptation Lab : Exploring DA MNIST and MNIST M
View Projectagentic_framework_file_organizer
February 16, 2025 – February 16, 2025
File Manager with AI Agent: A Python-based file management system with an AI agent that automatically organizes and compresses files based on their types.
View Projectshakespeare-style-text-generator
January 18, 2025 – January 18, 2025
This is a transformer-based language model trained on Shakespeare's text. The model can generate Shakespeare-style text continuations from any prompt.
View ProjectStable_Diffusion_Text_Inversion
January 15, 2025 – January 15, 2025
Stable_Diffusion_Text_Inversion
View ProjectCustomNNLayers
January 14, 2025 – January 15, 2025
This repository contains implementations of custom layers and are built using PyTorch. As example CNN and Transformer model is trained
View Projecthindi-bpe-tokenizer
January 10, 2025 – January 10, 2025
This project implements a Byte Pair Encoding (BPE) tokenizer for Hindi text. The tokenizer is designed to efficiently encode and decode Hindi text while preserving spaces and providing detailed statistics about the tokenization process.
View Projectnamed_tuples
January 5, 2025 – January 5, 2025
This repository contains Python modules for handling and analyzing profile and company data using both named tuples and dictionaries, along with comprehensive test suites.
View Projectweb-notes-extension
October 12, 2024 – October 12, 2024
Google Chrome Extension for capturing notes from web pages on the go
View ProjectAI-Engineering-ERA3
October 12, 2024 – August 25, 2025
All things AI Engineering : Models, Transformers, LLMs, FrontEnd, BackEnd, Distributed Training, On Cloud
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong interest and self-driven initiative in cutting-edge AI/ML topics, which could indicate a good fit for an innovative and research-oriented culture. However, the projects are predominantly personal, and there is only one listed professional experience as a Data Scientist with no details on responsibilities or team collaboration, making a comprehensive cultural fit assessment challenging. The diversity of projects (file organizer, web notes extension) suggests a broad interest beyond core AI, but the primary focus is clearly on AI/ML.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a proactive and self-driven approach to learning and applying advanced AI concepts.