Abstract: The boom of generative AI and LLMs have taken the world by storm. This development has already disrupted various industries and roles, and data science is no exception to that rule. In a word of embeddings and transfer learning, one might beg to question "What should I learn next?" and "Where should I spend my time and energy for deep dives?". This talk aims to guide existing AI practitioners on how to maintain relevant skills in an increasingly automated world, and how to stand out in an oversaturated job market.
Bio: Leondra R. Gonzalez is a Sr. Data & Applied Scientist at Microsoft and Information Science / AI Researcher at the University of the Cumberlands with over 10 years of experience in data science. Over the course of her career, Leondra has practiced her passion for data science education by consulting for many companies including DataCamp, SpringBoard, Western Governor's University, and more. Currently, Leondra works on building NLP and propensity models to help determine the best cloud computing account executives execute enterprise deals. However, she has a wide range of experience across the entertainment, media, and tech spaces. Academically, she earned a BA at Otterbein University studying business, management, and music, followed by a Masters in Entertainment Industry Management, Business Analytics from Carnegie Mellon University, an MBA in Data and Decisions from Quantic School of Business and Technology, and is a PhD candidate in Information Technology with a Specialization in Artificial Intelligence, where she's researching AI governance and regulatory strategy. During her academics, she has interned for Amazon, Google, AT&T, NBC Universal, and more. She is releasing a book on mastering data science interviews in early 2024.
Currently, Leondra resides in Indianapolis, IN with her husband Chris and two cats.