goldman sachs

The interview process consisted of three rounds. In the first round, I started with a brief introduction, followed by an in-depth discussion of my projects. The interviewer asked me to describe my strongest project, explored my thought process, the challenges I faced, and my most significant achievement. They also presented several scenario-based questions to understand how I would approach different situations. The round concluded with a DSA problem and a behavioral question, and I felt confident about my performance, which helped me advance to the next round. In the second round, I again gave a brief introduction before the interviewer focused on another project from my resume, asking detailed questions about my technical decisions, such as why I chose specific approaches and technologies. Since the project was based on machine learning, I was questioned on machine learning concepts, along with libraries like Pandas and NumPy. Because I had listed DBMS on my resume, I was also asked questions on SQL and core database concepts, particularly the ACID properties, including atomicity and their practical applications. In addition, I was asked to write the Quick Sort algorithm, solve another DSA problem, and answer conceptual questions on data structures such as stacks and queues. In the final round, the interviewer discussed my third project, asking whether it was an individual or group project, my role, the reasoning behind my design choices, my overall thought process, and the outcomes or benefits of the project. I was also asked concepts related to static inner classes and inheritance in Java, followed by a design question in which I had to implement a HashMap from scratch.