Megan Tang is a results-driven Data Scientist with 7 years of experience in developing and deploying machine learning models, specializing in Natural Language Processing (NLP) and predictive analytics. Currently based in Austin, TX, she is passionate about translating complex data into actionable insights and innovative AI-driven solutions. Megan possesses a strong background in statistical analysis, Python programming, and big data technologies. She is recognized for her ability to lead data science projects from conception to deployment, effectively collaborating with cross-functional teams to achieve business objectives and drive technological advancement. Megan is dedicated to continuous learning and exploring the ethical implications of AI.
Megan Tang's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Led a team of 5 data scientists in the development and launch of 'InsightAI', a predictive analytics platform that improved customer retention by 18% within the first year of deployment by identifying at-risk customers.
Developed and successfully patented a novel deep learning-based algorithm for sentiment analysis that achieved 92% accuracy on benchmark datasets, outperforming existing industry standards by 5%.
Selected to present research on 'Ethical Considerations in AI Model Training' at the International Conference on Artificial Intelligence, sharing insights with over 500 industry professionals and academics.
Co-authored a peer-reviewed paper titled 'Advancements in Unsupervised Learning for Anomaly Detection' detailing a new methodology for identifying outliers in large-scale financial datasets.
University of Chicago - Year 2011
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