Hey! I’m Emmanuel, Data Scientist & Engineer

I am a Business Intelligence Engineer at Amazon conducting research/analyses, building models and identifying insights to drive ASIN Conversion through Causal AI, Machine Learning, and Statistical Modeling. I craft POCs that blend data pipelines, ML frameworks and business intelligence solutions to drive better customer experience at Amazon US Stores.

I’ve earned my Masters in DataScience from UT Austin whilst working full-time, studying the math and understanding the logic behind every ML algorithms and principle.
I excel at solving problems and enjoy learning new things, especially in fast-paced environments. Currently, I am learning and exploring deep learning by building vision-based self-driving agents for racing simulators. I am also experimenting with different techniques and algorithms, such as LLMs, RAGs, and prompt engineering, to stay updated in this ever-evolving field.
In my previous professional role, I served as a Data Scientist, developing new credit underwriting models by constructing predictive models using XGBoost to forecast the likelihood of loan delinquency for customers in specific loan portfolios under U.S. subprime market conditions.
Took ownership of an analytics project and successfully generated 400,000 dollars in revenue every month. Participated in multiple intra-organisation hackathons at Applied Data Finance by building new credit models to filter out fraudulent customers and maximise the revenue earned through loan interests (Won 2/4 hackathons, and was placed 2nd in the other two; Team effort).
Earned my Bachelor’s degree in EC from the Indian Institute of Information Technology, Chennai.

Juggling work n Studies

Outside of Work

🔭 I’m diving deep into the latest research papers on LLMs, Causal Inference(s), Prompt-Engineering, RAG, AI Agents to stay up-to date in these ever evolving fields. I try to comprehend the thoughts and processes underlying the content of these papers.
🌱 I apply any newly encountered tech stacks from my readings to various datasets, gearing up for future roles that leverage these technologies.
🤔 I’m planning to dive deep into RAGs, LLMs and building AI Agents. My intention is to apply these concepts in projects, as I believe that hands-on experience and application are more effective in enhancing understanding compared to mere reading. Recently, I’ve created a notebook of an conversational agent using Langchains, RAG, and LLM.
😄 I’ve built vision based racing simulator system and a RL-DL agent to play SuperTuxKart Ice Hockey as part of my Masters program. The challenge was tough but I learnt a lot from the basics of neural layers all the way to deep neural networks.
😎 I occasionally engage in Speedcubing, finding it to be a mental stimulant that enhances my thinking abilities and an excellent means of relaxation. Good at solving the Pyraminx (Former National Runner-up 2018)! I was once ranked 3rd in India, 10th in Asia, 32nd in the World. Owing to tighter schedules, I attend competitions rarely.

pyraminx ranking