Engineering professional with 11+ years of industry experience, currently focused on Data Science, Machine Learning, and Artificial Intelligence. Strong background in software engineering and cloud-based systems, with hands-on experience in ML modeling, Deep Learning, NLP, and data engineering.

• Machine Learning & Data Science projects
• Data Engineering with AWS
• Neural networks implemented from scratch

• Python (NumPy, Pandas, Scikit-learn, TensorFlow), SQL
• Machine Learning (Linear Regression, Logistic Regression, Support Vector Machines, Unsupervised Learning, Dimensionality Reduction)
• Deep Learning (Neural Networks, Back Propagation, Regularization and Optimization, Convolution Neural Networks), Deep Reinforcement Learning
• Natural Language Processing (NLP) - N-gram and Neural Language Models, LLM, Prompt Engineering, Skip gram/CBOW, BERT, Retrieval Augmented Generation (RAG)
• Data Visualization (Matplotlib, Seaborn, Tableau)
• Statistics, Probability, Linear Algebra, Optimization
• Amazon Web Services (AWS), S3, IAM, EC2, Lambda, SQS, SNS, AWS CloudWatch, AWS Glue, Amazon Redshift, Amazon Athena
• Agile Development, Git, Azure DevOps, GitHub Copilot

• Random Length Pricing (ML/Data Science)
• Deep Neural Networks from Scratch
• N-gram Language Model (NLP)

📫 Open to ML Engineer / AI Engineer / Data Scientist roles