Tune in, and get inspired with WiDS

This podcast episode features Sohini Sarkar, Principal Product Manager and Senior Team Lead at MathWorks, discussing her career journey and offering advice to listeners. The conversation explores her transition from academia to the corporate world, her passion for product management, and her approach to balancing technical expertise with leadership responsibilities. Sohini’s career path highlights the importance of self-discovery and the willingness to deviate from predetermined expectations.

Claudia Perlich, a leading expert in predictive modeling shares about her work and views on the challenges of using AI and machine learning systems. Perlich discusses the importance of understanding the uncertainty and biases inherent in these models, and the need for careful evaluation and testing before deploying them, especially in high-stakes domains. She emphasizes the collective responsibility of data scientists, domain experts, and decision-makers to ensure these systems are used responsibly and equitably. She also shares insights on the skills and mindset needed for a successful career in predictive modeling, highlighting the value of data curiosity, scientific thinking, and effective communication.

Huda Nassar is a data scientist who did her PhD at Purdue University, advised by David Gleich. Her research focused on graph alignment, using a combination of mathematics and computer science to solve real-world problems. After completing her PhD, Nassar did a postdoc at Stanford and now works at the company RelationalAI, where she develops optimized graph algorithms to help customers. Nassar is passionate about the intersection of mathematics and programming, and advocates for students to take courses in both areas. She also enjoys teaching and is a proponent of the Julia programming language. Nassar discusses how finding the right mentors has been crucial to her academic and career journey.

In this podcast episode, Hannah and Chisoo discuss their shared experiences as immigrants and how that has shaped their perspectives and careers. They explore the value of learning new languages and being immersed in different cultures, as well as the importance of understanding problems before jumping into solutions when working in data science. Hannah shares her leadership philosophy of prioritizing people development, and they both emphasize the need to address burnout and create flexible work environments, particularly for women in the field. The conversation highlights the evolving nature of data science and the opportunities for the next generation of women to thrive in this dynamic industry.