Daisy Lee is a distinguished Principal Data Scientist with 12 years of experience in crafting and deploying impactful machine learning models and data-driven strategies for tech and e-commerce sectors. Based in Austin, Texas, she excels in translating complex business problems into scalable AI solutions using Python, R, SQL, and various cloud platforms. Daisy is recognized for her leadership in building high-performing data science teams, her contributions to ethical AI frameworks, and her ability to communicate intricate technical concepts to diverse audiences. She is deeply passionate about leveraging data to uncover insights and drive innovation.
Daisy Lee's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Architected and led a team to develop a novel recommendation engine that increased customer engagement by 25% and sales conversion by 15% for a leading e-commerce platform.
Co-authored a highly-cited paper in the 'Journal of Machine Learning Research' on identifying and mitigating bias in predictive algorithms, influencing industry best practices.
Awarded 'Innovator of the Year' by her previous company for pioneering a new fraud detection system that saved the company an estimated $5 million annually.
Delivered a keynote address on 'The Future of Explainable AI' at the DataScienceGo 2022 conference, sharing insights with over 1,500 data professionals.
University of California, Davis - Graduate School of Management
University of Colorado Boulder
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Arrow Electronics is a global provider of products, services, and solutions to industrial and commercial users of electronic components and enterprise computing solutions. Arrow serves as a supply channel partner for over 220,000 original equipment manufacturers, contract manufacturers and commercial customers through a global network. The company guides innovation forward for producers and users in markets ranging from aerospace and defense to transportation and industrial.
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