Test: The test comprised three sections. The first section had quant and aptitude MCQs, the second required a basic understanding of ML through MCQs, and the last section was an optional case-solving part. To excel, it is crucial to have good math skills and practice time management to attempt as many questions as possible with accuracy. Specific preparation tailored for Amex was not required. Practice aptitude from Prepleaf (website) and solve quant puzzles (refer to “Heard on the Street” and “Practical Guide to Quant Finance Interviews” by Xinfeng Zhou). Regarding difficulties, the case section was initially new to me and took some time to grasp (with its unique interface). However, the other sections can be cracked easily with general quant and aptitude preparation. The Interviews: I went through two rounds of interviews. In the first one, I was asked to introduce myself and explain why I chose analytics after a degree in Architecture. Later, I discussed a technical project from my CV that I enjoyed the most, addressing general questions and any difficulties I faced. Additionally, thorough research about American Express and its business model proved essential. I was asked about its distinctiveness compared to competitors and given a task to outline criteria for assessing the credibility of a person applying for a credit card. The second interview was more technical, involving a statistical question on paper with graphs. I was questioned on the process I would follow to obtain specific results, among other inquiries.