I’m a full-stack Data Scientist with a deep passion for solving high-impact business problems through machine learning, experimentation, and analytics.
Previously at Amazon, I specialized in designing forecasting and pricing optimization frameworks that guide multi-billion-dollar product strategies. From conjoint analysis and willingness-to-pay modeling to time series forecasting and inferential analysis, my work helped launch and grow Amazon Devices in a data-driven way. I’ve built and deployed end-to-end ML solutions across companies—driving efficiencies through AutoML platforms, real-time inference APIs, and big data pipelines using tools like Spark, Kubeflow, and Docker.
đź’ˇ I love exploring innovations in Deep Learning, LLMs, and NLP, and building intelligent systems that scale.
    🎓 MS in Data Science – University of Washington
    📍 Based in Seattle | Open to collaboration, mentoring, and innovation