Who I Am
About Me
Data Scientist, community builder and lifelong learner based in Manhattan, New York.
Currently
Pursuing MS in Data Science
Columbia University, NY
My Story
I help machines
learn smarter
Hey there, I'm Ayon Roy, an AI Researcher and MS Data Science student at Columbia University. My work spans Edge AI Quantization (Qualcomm), Generative & Agentic AI Systems (Columbia), and Multi-Modal / Geospatial Machine Learning (NielsenIQ). I specialize in ONNX runtime optimization (AIMET-ONNX), LLM orchestration, Knowledge Graphs (AWS Neptune), and translating complex data into scalable intelligence.
I served as an Executive Data Scientist at NielsenIQ's Global Centre for Statistical Research and Data Science for 2 years. Prior to that, I served as a Data Scientist in NielsenIQ's India Data Science Business Leaders team working with the biggest FMCG players in the world.
I founded India's 1st & Largest Kaggle Days Meetup community, reviewed 4 published technical books, have mentored and judged 115+ hackathons, and delivered 100+ technical talks worldwide. Having helped 3,950+ people start their Machine Learning journey, I genuinely believe in the power of community learning. I remain dedicated to helping "artificial brains" reach their full potential through adaptive problem-solving and scalable, real-world data strategies.
Value Proposition
How I Play with Data
My expertise spans the full data science pipeline — from problem framing to production deployment.
Predictive Modelling
Regression (Linear, Logistic, Polynomial, Ridge, Lasso), ARIMA & LSTMs for time-series forecasting, ensemble methods.
Computer Vision
Object detection (YOLO), image segmentation, satellite imagery analysis using OpenCV, TensorFlow and PyTorch.
NLP
Text preprocessing, feature extraction, similarity detection, sentiment analysis and transformer-based approaches.
Data Pipelines
End-to-end data gathering, cleaning, feature engineering and model deployment at scale for real customer impact.
Analytics & Insights
EDA, business hypothesis testing, experimentation analysis and storytelling that drives decisions.
Research
Reading, extracting and implementing insights from recent research papers. 4 technical books reviewed.
Looking for a Data Scientist?
If you have opportunities, crazy product ideas, or want to collaborate — reach out. I'd love to chat.