Underclassmen Fellowship

The process started with an online assessment focused on statistics. It included six quantitative questions testing probability, distributions, and basic analytical reasoning. After that, I completed a Python-based assessment centered on simple modeling tasks. The problems were straightforward but required clear code structure and an understanding of how to translate a statistical idea into a small script.

After the assessments, the firm scheduled two rounds of interviews. The first was technical, covering probability, expected value, modeling intuition, and a brief walkthrough of my Python OA approach. The second was behavioral and focused on how I think, how I handle uncertainty, and how I work with others. Both interviews were structured but conversational.

The coordination was smooth, with quick communication and clear instructions for each step. The people I interacted with were direct, analytical, and respectful. The culture came across as focused and quantitative, with an emphasis on clear thinking and intellectual honesty.

Advice: review core probability concepts, practice small modeling tasks in Python, and be ready to explain your reasoning simply. For behavioral questions, emphasize clarity, curiosity, and how you approach open-ended analytical problems.