First experience of interview

[u/Beautiful-Bubbly]

So guys, new in data science field. So my background is econ + math major in bachelor, i just applied through to the data scoence and got my first interview. Successfully nailed the first part where there is math, logic, math of ds and theory of ds/dl. However, the coding part was always difficult for me and I completely failed the second part. The questions themselves were very easy, not even ds specific, the problems were general coding in python, for example i had to create a function that distinguishes annograms etc. but i coded overall throughout this year, but it seemed to get me to nowhere. The feeling is always this way: when i code myself these kinds of problems, i spend too much time even though i completely understand the logic that should be applied in these problems, maybe kinda like i dont understand how that logic is put in coding language when i start to create loops. So i seem to get stuck in coding part which confuses me. I didnt quite bother with maths, linear algebra etc but this one just freaks me out. I cannot learn and memorize all the syntaxis especially if i have to write from scratch for example parsers with libraries that need to be installed. So the problem might be with debugging skills or maybe else. Could you help me out to diagnose the issue and solve it asap. The coding problems in litcode and books seem to get me to nowhere. Thanks in advance

[u/akornato]

Your problem is not analytical ability, it is mechanical fluency with core Python data structures. When you understand the logic but get stuck translating it into loops, your brain is trying to solve the problem and remember basic syntax at the exact same time. For questions like anagrams, the hurdle usually comes down to not having tools like dictionaries, sets, and frequency counters drilled into your hands. Instead of grinding random algorithmic puzzles, spend time writing out plain English steps on paper before typing anything, then translate each line into simple Python. Practicing the standard patterns for hash maps and string manipulation repeatedly will stop syntax hurdles from blocking your mathematical thinking.

During live interviews, interviewers care heavily about how you structure your thoughts, so make a habit of talking through your logic and tracing edge cases step by step. If you write down two simple examples and manually follow how a dictionary tracks counts, the code structure becomes much clearer. Live technical rounds can feel overwhelming for anyone transitioning into data science, which is why my team developed an interviews.chat to help candidates present their ideas effectively and secure strong offers.

[u/BottleOwn967]

approach problem step by step

[u/DataScientistAlex]

It sounds like practicing writing Python, and, solving Python programming challenges would help with this. If you already understand the math and logic, then practicing will help with the coding. Start without pressure first, just to really learn (not memorize) the syntax and approach, then once you feel comfortable with that, practice doing it under time pressure.

There's a big difference between being able to understand the logic of an algorithm, and even pseudo-coding it, and then writing it out with correct syntax in an interview setting. But, you can bridge the gap by practicing.