Todo bien. Llenas tu solicitud en su portal . Primeramente te dan una entrevista con RH, luego te dan pruebas para que las completes y finalmente hay una entrevista técnica.
Domande di colloquio [1]
Domanda 1
Que tipo de pruebas has usado para predecir los datos
Ho presentato la mia candidatura online. Ho sostenuto un colloquio presso Thomson Reuters
Colloquio
Platform: HackerRank is a widely used technical assessment platform.
Duration: 45 minutes total.
Question Type: 29 MCQs — these are typically conceptual or theoretical questions that test your understanding of programming, data science, statistics, or domain-specific knowledge.
No coding questions (based on your description), which means the focus is likely on knowledge recall, problem-solving, and analytical thinking.
Ho presentato la mia candidatura tramite un'altra fonte. La procedura ha richiesto una settimana. Ho sostenuto un colloquio presso Thomson Reuters nel mese di dic 2024
Colloquio
Recruiter reached out to me for data scientist role out of bangalore. told me about the recruitment process, which included a technical round, hiring manager round, HR round. technical round would have included a coding session for 1 hour, as per the recruiter's understanding. i am based out of US so timing the technical round was tough. my first interview was scheduled for wednesday for 1 hour, which was unexpectedly pushed to friday at 4:30AM (my time). i again asked the recruiter what can i expect in this interview, he emphasized that it will be a coding round.
There were 2 interviewers, M and F, they began the interview with something like an ML deep-dive. the recruiter failed to mention to me about any such interview. M left the call and went somewhere in the middle of the interview. in the mean time, F asked me a couple of questions. when M returned, he asked me the same questions again. They abandoned the meeting after 30 mins. no coding session was conducted. no feedback provided.
Domande di colloquio [1]
Domanda 1
multicollinearity, correlation, covariance, random forest, decision trees, bias-variance tradeoff, precision, recall, F1 score, imbalanced data, cross-validation, overfitting, regularization, one-hot encoding, ordinal encoding, bagging, boosting, which models support multicollinearity.
