General interview and after sent tech task (quite standard: some data preparation + ordinary ML). It was quite simple for my level (I am highly skilled and experienced). After some my additional questions about requirements (which were totally ignored) HR told me to use instructions in filename and only them. After I submitted solution (extensive and solid one) I was quickly rejected without any solution discussion, additional questions or explanation. I was highly surprised and requested a feedback. In it in passive-aggressive manner there are several points and comments a la "from a dozen possible ways to do thing you choose not the one I prefer and that's why It's completely wrong", and points in it that are not total nonsense were not specified in the requirements (although nonsense ones also were not). Although the quality of model and data preparation itself was not questioned. Checking out again I found out that HR pointed out at the wrong filename with instructions! I have a lot of files in downloads and didn't noticed another one, suddenly there are two of them. My mistake but I definitely would not do it if not for those wrong directions. However only 2 points from their report were covered by this newly discovered file (small tasks on basics, clearly from my resume I can do it). The other 5 remained or the same nonsense, or just non-obvious, unnecessary and in need to be clearly specified before if they want to see them in solution. Ha. I tried to speak with HR about this situation and she didn't reply me, and also tried to contact with higher management with the same outcome. I have some obvious thoughts of what happened. And no doubt this is one of the most indifferent and incompetent attitude to best talents I have ever seen.

The interview process was straightforward and well organized. It started with a recruiter screening about my background and interest in the role, followed by a technical interview covering SQL, Python, statistics, and machine learning concepts. There was also a case study discussion where I explained my approach to analyzing data and communicating insights. Overall, the process was average in difficulty and focused on practical data science skills.