Goldman Sachs Data Analyst Interview Guide

Candidates who interviewed specifically for the Goldman Sachs Data Analyst role describe a process anchored in practical analytics work rather than heavy algorithm drills. Both Data Analyst reports start with a screening conversation about background, motivation and SQL experience. One candidate then faced a technical round on writing SQL queries, cleaning data, building dashboard reports and presenting insights to stakeholders, including how they would work through a large dataset to find useful business insights. The other describes two screening rounds in which basic SQL, join types and a walkthrough of a past data project were central. The second round placed more weight on SQL and closed with two situational questions. Neither candidate received an offer, and two reports is a thin base, so treat this as a likely shape rather than a fixed format.

Reports from Summer Analyst tracks at Goldman Sachs mention HireVue videos, Superdays and coding or math assessments. Those are different tracks, so use them only as loose context.

For preparation, be able to explain each join type and when you would use it, not just its definition. Rehearse one end-to-end project story: the question, data cleaning, analysis, visualization and the decision it supported. Prepare behavioral examples on teamwork, deadlines and explaining results to non-technical stakeholders. Keep your answers about motivation and experience consistent and specific, since one candidate noticed the same questions repeated across rounds.