I started with a coding-focused hangman take-home assignment. It came with performance expectations: clearing a minimum level would earn an invitation to the superday. The assignment included a hangman strategy described as a baseline, along with typical win rates and the expectation that I beat it.
After I finished, I had a round focused on my solution and my Python implementation choices, including details such as how I handled arrays. They also asked how I had reasoned through the project, not just whether it worked. The hangman experience felt high pressure, and I found the allowed approaches somewhat restrictive.
Once that technical foundation was in place, the process moved to broader onsite evaluation. The questions connected back to my background and how I thought about modeling and learning. What surprised me was that the hangman work wasn't treated as a side task. It was a core measure of whether I could build and explain a quantitative solution. I didn't get an offer, but the process still felt coherent. The hangman task set the tone, and the follow-up rounds tested whether I understood the tradeoffs.
Location: Gurgaon, Haryana. Overall feedback: Neutral. Offer status: No offer.
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