Introduction
I am a data science professional with 2+ years of professional experience at delivering AI solutions at scale. I possess rock-solid fundamentals in machine learning, deep learning, generative AI, and in using industry-leading practices and frameworks like Python, Pyspark, Pytorch, Github, and Google Cloud Platform to build AI driven products - right from model development till deployment.
Core Skills and Expertise
- Languages: C/C++, Python, SQL, R
- Libraries: numpy, pandas, scikit-learn, matplotlib, pytorch-geometric
- Frameworks: Autogluon, Apache PySpark, PyTorch, Kubernetes Flow Pipelines
- Developer Tools: Git, Docker JupyterLab, Google Cloud Platform, Vertex AI, Visual Studio Code, GitHub Copilot
- Large Language Models (LLMs): langchain, langfuse, ChromaDB, llamaindex
Work Experience
- Built an optimization engine for route selection using PuLP. Obtained 11% cost reduction over the traditional heuristic allocation, leading to savings of more than $1.1M on import purchase orders annually.
- Spearheaded the development of a Graph Neural Network model to develop embeddings for a downstream link prediction task. Achieved 75% mAP and 78% recall on an unknown interaction dataset.
- Led the development of a causal ML model for use in hyper-personalized marketing campaigns. Obtained 70% of predicted sales while utilizing only 32% of the allocated discount markdown.
I'm looking for...
Data scientist/ML Engineer/AI Engineer roles, owing to my experience in developing AI solutions and deploying them at scale. I have a demonstrated history of taking models from notebooks to production, and possess a strong culture of constant and consistent innovation to deliver excellent products.