Gunjan Desai is a data scientist with seven years of experience applying machine learning and deep learning to advertising attribution, financial modeling, and large-scale time-series and geolocation problems. Currently at Warner Bros. Discovery, she combines production-focused analytics with a strong research background from NYU—where she fine-tuned BERT/FastText and deep recommendation models that outperformed linear and tree-based baselines. Her cross-industry experience spans media, finance, pharmaceuticals, and pandemic forecasting, demonstrating an ability to turn messy real-world data into actionable insights and deployable models. Notably, she has automated analytics pipelines in Hadoop environments and helped build forecasting tools used for county-level COVID simulations, reflecting both engineering rigor and domain impact. Based in Los Angeles, she brings a practical blend of academic research, teaching experience, and hands-on production delivery.
7 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Data Science, Information Systems, Master of Science - MS, Data Science, Information Systems at New York University
Bachelor of Engineering - BE, Computer Science, A, Bachelor of Engineering - BE, Computer Science, A at University of Mumbai
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