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Senior Data Science Engineer with over 4 years of experience in Data Science, AI, Machine Learning, and MLOps. At Azuga, I lead cloud operations, data architecture, and MLOps, focusing on scalable AI solutions for real-time data processing. My key projects include the Accident Risk Survival Model, the NLP Sentiment Analysis Algorithm, and a real-time streaming data warehouse. Additionally, I developed a Generative AI-based "Chat with Data" project to enhance user interactions through conversational AI.
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Previously, as an Analytics Engineer at Simplilearn, I managed data reports, conducted quality audits, and worked on statistical analysis projects. I also provided consulting services on Data Science projects for Purdue and UMass clients. At Pianalytix, I led machine learning initiatives aimed at client retention, utilizing advanced algorithms and real-time integration.
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During my internship at Dhirtek Business Research & Consultancy, I focused on statistical modeling to predict market growth in Liquid Biopsy treatments. My research papers, one on Predictive Maintenance Using Machine Learning Techniques, has been accepted for publication in the IEEE Journal and and another on Supply Chain Optimization was published in International Journal of Applied Engineering and Technology (IJAET) . These papers highlight my expertise in applying machine learning to solve real-world challenges in maintenance and logistics.
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With a passion for AI, machine learning, and MLOps, I am committed to advancing innovations in data science and automation.