Streebo Interview Questions
& Process

First up was a chat with HR about your background and resume, plus basic stuff like communication skills, salary expectations, and when you can start. Then there was a technical interview diving into QA fundamentals, covering testing types (manual, automation, regression, unit, integration), and asking scenario questions like how you'd test a login page. They also asked about tools like Selenium, JIRA, TestRail, and how you report bugs. Sometimes they throw in a practical assignment to test your skills, like writing test cases or finding bugs. Finally, a managerial or client-facing chat to see how you solve problems, talk to developers, and handle client needs, like prioritizing bugs near a release. The last step was another HR chat about company culture, growth, and finalizing the offer.

It was a college Placement Drive. First, HR conducted a pre-placement talk. After that, an Aptitude test was conducted, and only 20% of candidates made it to the second round. The second round was the HR round, and only 23% of candidates secured a spot for the last round, which was the Technical evaluation round. I solved both coding questions but couldn't answer 2-3 interview questions. In the HR round, I was asked to write the syntax of an array and a program for the Fibonacci number series. Overall, the experience was good, and it was my first interview. My tip for candidates applying to this company is to review core Java concepts and Java basics.

So I interviewed with Streebo and it was pretty good. They asked me stuff about OOPs concepts, Machine Learning basics, and some simple coding problems like Fibonacci and factorial implementations. The interview panel seemed to want to check if I knew my programming fundamentals and if I could apply them. The OOPs questions were pretty standard, like about inheritance, polymorphism, abstraction, and so on. The Machine Learning questions were more theory-based, not a lot of coding or project stuff. The coding part was basic, just to see if I could build logic. Overall, it was moderately difficult, a good mix of theory and practice. It's good because it covers the fundamentals well and balances coding with concepts, which is helpful if you have strong basics. But, it wasn't very deep on practical ML questions, focusing more on theory than hands-on. So, if you're getting ready, focus on core OOPs concepts, ML fundamentals, and basic coding problems. Having a solid foundation is more important than advanced knowledge here.

So, first there was an online aptitude test. It had DI and quant, logical reasoning, and computer fundamentals. Then came the HR round, but surprise! Instead of typical HR questions, they asked coding questions and oops concepts. Nobody told us about this, and we were all prepped for normal HR stuff. The third round was a coding round.