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Hello, I'm Xilin Wang, a recent M.S. graduate in Financial Engineering from Columbia University. I work at Columbia Plus, developing Generative AI content for online learning. I graduated cum laude with a B.S. in Operations Research from Columbia University and also hold a B.A. in Mathematics from Bard College.

I have extensive experience in machine learning and quantitative finance, with a strong focus on deep learning and Generative AI, particularly in financial applications. I have hands-on experience researching and building Retrieval-Augmented Generation (RAG) chatbots for educational and commercial purposes, utilizing platforms such as AWS, Google Cloud, OpenAI, and LangChain. My technical skills include proficiency in Python, Spark, C++, Scala, SQL, and R, as well as libraries and frameworks like TensorFlow, PyTorch, scikit-learn, and Pandas.

My professional background includes roles such as AI Researcher at Columbia Plus, Quantitative Research Intern at Lockwood Analytics and CITIC Securities, and Research Intern at ask2.ai. In these positions, I developed deep learning models, conducted machine learning research, and implemented data-driven solutions to enhance financial strategies and model interpretability.

In addition to my technical skills, I excel in communication and teamwork. My past teaching and peer counseling experience have honed my ability to mentor and lead.

For more about my work and experience, you can visit my LinkedIn profile. Feel free to reach out if you're looking for someone motivated, ambitious, and fun at [email protected].