SIG (Susquehanna) Data Scientist interview questions typically blend quant-driven problem solving with applied data science tasks, so interview preparation should cover probability, statistics, and coding as well as domain intuition. What’s distinctive about SIG’s hiring for data roles is the emphasis on rapid quantitative thinking and clear tradeoff reasoning: expect probability and expected-value puzzles, SQL and Python exercises, short modeling or A/B analysis problems, and conversations about how you would turn insights into reliable, production-ready signals. Interviewers look for analytical rigor, clean communication, and the ability to balance statistical correctness with operational constraints. In practice you should expect an initial screen and timed online assessment, followed by technical interviews and a final on-site or “super day” that may include a case or take-home data exercise. Prepare by practicing probability puzzles, coding problems under time pressure, end-to-end analyses that include data cleaning, metrics, and interpretation, and concise explanations of assumptions and failure modes. Mock interviews and rehearsed storylines about past projects help you demonstrate impact and ownership.