Technical discussion on background, take home Data Science problem testing data wrangling, data processing, feature engineering, model development, validation and testing, with visualizations. problem statement presentations - one or two, ML interview covering various concepts of ML, Deep Learning and cloud knowledge (if any) in depth
Domande di colloquio [1]
Domanda 1
How did you pre-process data for sentiment analysis project?
Ho presentato la mia candidatura tramite l'università. Ho sostenuto un colloquio presso Quantiphi (Bengaluru) nel mese di ott 2025
Colloquio
Not that much tough . If you have learn ml neither as a pro or as a beginner . You can get that opportunity by just reaching out to interview process . 1 st interview will online that will culture fit round and 2 nd round will offline than a online hr interview in the end .
Ho presentato la mia candidatura tramite l'università. Ho sostenuto un colloquio presso Quantiphi (Bengaluru) nel mese di ott 2025
Colloquio
First round - Basic Python coding questions like sort the dictionary, input output,swap the item in dictionary , sort the dictionary according to values, sort the dictionary in descending order
then project discussion
Ho presentato la mia candidatura tramite l'università. Ho sostenuto un colloquio presso Quantiphi (Mumbai) nel mese di set 2025
Colloquio
1. OA consists of logical reasoning, quant, English, and three DSA questions
In DSA, one was one array manipulation (easy), two pointers, and the last one was a graph question
Domande di colloquio [1]
Domanda 1
Resume-based, detailed explanations of your projects, core concepts of Machine Learning, different regularization/ activation functions, different models and their architecture