Super Data Science: ML & AI Podcast with Jon Krohn 006: Financial Modeling and Data Science, Inputs vs Assumptions and Going Big with Xinran Liu
Oct 16, 2016
Expert Financial Modeler Xinran Liu discusses financial modeling, data science, inputs vs assumptions, and collaborations between the two fields. They dive into valuing companies, sensitivity analysis, the importance of assumptions, and distinctions between industry and consulting work.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8
Intro
00:00 • 5min
Recalling Past Work Experiences and Collaborations in Financial Modeling and Data Science
05:14 • 2min
Navigating through Financial Modeling in Consulting and Industry Transition
06:53 • 10min
Financial Modeling and Data Science Collaboration in Valuing Companies
16:32 • 19min
Exploring Tornado Charts and Input Sensitivity in Financial Modeling
35:27 • 2min
Importance of Assumptions in Financial Modeling
37:07 • 8min
Industry vs. Consulting: A Comparison
45:37 • 4min
Insights on Career Development, Financial Modeling, and Data Science
49:41 • 4min