Lead Data Scientist || LLM/RAG Expert || AI Solutions Architect
My Journey in Data Science and AI
With over seven years of experience in the field, I’m passionate about using data and AI to create a better, more sustainable future. I thrive in environments that value innovation and progress, and I find immense satisfaction in tackling complex challenges and transforming them into impactful solutions.
Currently, I’m leading AI efforts at Avathon, where I’ve led the development of industry-relevant foundation-model MLops platforms, built agent platforms with MCP tools, and launched RAG compliance solutions. My work has resulted in significant improvements including 45% faster release times, 25% reduction in false positives, and over $500k in customer savings through anomaly detection systems.
Before my current role, I developed my skills at Texas A\&M University, researching machine learning to predict wind energy system failures under Dr. Yu Ding. I also gained experience at Utilities and Energy Services, creating weather-controlled baseline regression models for digitally metered utilities.
I’m passionate about using AI for positive change. My goal is to build AI solutions that make the world better, especially in areas like sustainability. I served as a Data Ambassador at DataKind, where I collaborated with John Jay College to develop machine learning models for predicting student dropout.
I’m eager to connect with others passionate about data and AI. Let’s collaborate to drive positive change with data-driven solutions.
Skills
Data Science & Machine Learning
Core Competencies:
Predictive Modeling & Analytics, Time Series Forecasting, Anomaly Detection
Deep Learning (CNN, RNN, LSTM, Transformers), Supervised & Unsupervised Learning
Large Language Models (LLM): Fine-tuning, Retrieval-Augmented Generation (RAG), Agents
Model Optimization, Hyperparameter Tuning, Feature Engineering