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Quantium Analytics Interview Questions and Answers

Updated 18 Nov 2024

Quantium Analytics Interview Experiences

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4 interviews found

Interview experience
1
Bad
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(2 Questions)

  • Q1. Explain kubernetes on GKe ?
  • Ans. 

    Kubernetes on GKE is a managed Kubernetes service provided by Google Cloud Platform.

    • GKE stands for Google Kubernetes Engine.

    • It allows users to deploy, manage, and scale containerized applications using Kubernetes.

    • GKE provides features such as automatic scaling, monitoring, and logging.

    • Users can easily create Kubernetes clusters on GKE using the Google Cloud Console or command-line tools.

    • GKE integrates with other Google...

  • Answered by AI
  • Q2. Are you aware Application Servers
  • Ans. 

    Yes, Application Servers are software frameworks that provide an environment for running web applications.

    • Application Servers manage the execution of web applications

    • They provide services such as security, scalability, and resource management

    • Examples include Apache Tomcat, JBoss, and Microsoft IIS

  • Answered by AI
Round 2 - One-on-one 

(2 Questions)

  • Q1. Explain about google cloud ?
  • Ans. 

    Google Cloud is a suite of cloud computing services provided by Google.

    • Offers a wide range of services including computing, storage, networking, machine learning, and more

    • Provides tools for data analytics, machine learning, and artificial intelligence

    • Allows users to build, test, and deploy applications on Google's infrastructure

    • Offers scalable and flexible pricing options based on usage

    • Examples: Google Compute Engine,

  • Answered by AI
  • Q2. Explaon bigquery architecture ?
  • Ans. 

    BigQuery architecture is a serverless, highly scalable, and cost-effective data warehouse designed for big data analytics.

    • BigQuery separates storage and compute, allowing for independent scaling of each

    • It uses a distributed architecture to process queries in parallel for fast results

    • Data is stored in Capacitor, a proprietary storage format optimized for analytical processing

  • Answered by AI

Skills evaluated in this interview

Cloud Operations Engineer and Senior Analyst Interview Questions asked at other Companies

Q1. Are you aware Application Servers
View answer (1)
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

It was easy and basics of aptitude and sql required

Round 2 - Case Study 

You need smart work here to analyze the given question

Data Scientist Interview Questions asked at other Companies

Q1. for a data with 1000 samples and 700 dimensions, how would you find a line that best fits the data, to be able to extrapolate? this is not a supervised ML problem, there's no target. and how would you do it, if you want to treat this as a s... read more
View answer (5)
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Basic math questions
Round 2 - HR 

(1 Question)

  • Q1. Basic hr questions

Data Scientist Interview Questions asked at other Companies

Q1. for a data with 1000 samples and 700 dimensions, how would you find a line that best fits the data, to be able to extrapolate? this is not a supervised ML problem, there's no target. and how would you do it, if you want to treat this as a s... read more
View answer (5)
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Indeed and was interviewed in Dec 2023. There were 3 interview rounds.

Round 1 - Aptitude Test 

Some simple math questions, mainly table and graph interpretation

Round 2 - HR 

(2 Questions)

  • Q1. Tell us about yourself
  • Q2. What would you do in certain situations
Round 3 - Technical 

(1 Question)

  • Q1. Case study followed by Q&A with the interviewer

Interview Preparation Tips

Interview preparation tips for other job seekers - For the behavioural stage, prepare to answer stuff in the STAR format.
For the technical round, read up about GBMs and GLMs

Junior Data Analyst Interview Questions asked at other Companies

Q1. What is the main difference between data mining and data analysis?
View answer (4)

Quantium Analytics interview questions for popular designations

 Data Scientist

 (2)

 Cloud Operations Engineer and Senior Analyst

 (1)

 Junior Data Analyst

 (1)

Jobs at Quantium Analytics

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Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. What friends think of you?
  • Ans. 

    My friends think of me as reliable, supportive, and always up for a good time.

    • Reliable - always there when they need help or support

    • Supportive - willing to listen and offer advice

    • Fun-loving - enjoys socializing and trying new things

  • Answered by AI

Interview Preparation Tips

Round: Resume Shortlist
Experience: After Resume Shortlist we had an aptitute round.
Tips: Answer according to your own judgement. Dont try to be too precise.

Round: HR Interview
Experience: I said they think I am a workaholic as I prefer to complete my work before chilling with them.

College Name: NIT Durgapur

Interview Preparation Tips

Round: HR Interview
Experience: Interview at 11 pm. Stressed environment, close to stress interview.
SELECTION PROCEDURE:
1.Online Test
2. GD
3. PI(HR)
GD TOPICS :
Topic 1 : How can education system benefit from interdisciplinary methods.
Topic 2 : Interconnected problems in the field of movie making.
INTERVIEW EXPERIENCE:
So you can speak German? Describe MS Dhoni in german. They opened Google Translate to counter check the words they wanted to be translated in both Deutsch and Spanish. Your profile speaks of an inclination towards software skills, why do you want to join an analytics company? Justify your action in two reasons as to why are you sitting here interviewing for the post of a data scientist rather than apply for a software engineer when this CV speaks highly of computer science? What is Finite Element Method? Explain. How relevant is your work in Computer Vision? Breakdown the tagline of Audi and translate accordingly. What is "Technik für Mobel" ? What are your current projects? Answer : Microsoft Xbox Kinect, Gesture Recognition. Counter question : But at Musimga you'd be doing far simpler stuff.? Counter suggestion : Why don't you go for MS?


Tips: Keep your cool during counter questions. Prepare your profile and CV well. Rest all is your hard work and groomed personal talents and acquired skills you learnt over the internet.

Skills: Ability To Cope Up With Stress, Spanish, German, Finite Element Modeling - FEM, Foreign Language
College Name: NIT Raipur
Funny Moments: Another HR enters in the midst of my interview and asks with bewildered amazement : What language is he speaking?
The other HR, "German".

I applied via Recruitment Consultant and was interviewed in Dec 2018. There were 3 interview rounds.

Interview Questionnaire 

11 Questions

  • Q1. 1. Why Machine Learning?
  • Q2. 2. Why did you choose Data Science Field?
  • Ans. 

    I chose Data Science field because of its potential to solve complex problems and make a positive impact on society.

    • Fascination with data and its potential to drive insights

    • Desire to solve complex problems and make a positive impact on society

    • Opportunity to work with cutting-edge technology and tools

    • Ability to work in a variety of industries and domains

    • Examples: Predictive maintenance in manufacturing, fraud detection

  • Answered by AI
  • Q3. 3. What about Linear Regression? (Theory Part)
  • Q4. 4. What is the difference between Linear Regression and Logistic Regression?
  • Ans. 

    Linear Regression is used for predicting continuous numerical values, while Logistic Regression is used for predicting binary categorical values.

    • Linear Regression predicts a continuous output, while Logistic Regression predicts a binary output.

    • Linear Regression uses a linear equation to model the relationship between the independent and dependent variables, while Logistic Regression uses a logistic function.

    • Linear Regr...

  • Answered by AI
  • Q5. 5. Explain Confusion Matrix?
  • Ans. 

    Confusion matrix is a table used to evaluate the performance of a classification model.

    • It is a 2x2 matrix that shows the number of true positives, false positives, true negatives, and false negatives.

    • It helps in calculating various metrics like accuracy, precision, recall, and F1 score.

    • It is useful in identifying the strengths and weaknesses of a model and improving its performance.

    • Example: In a binary classification p...

  • Answered by AI
  • Q6. 6. Can we use confusion matrix in Linear Regression?
  • Ans. 

    No, confusion matrix is not used in Linear Regression.

    • Confusion matrix is used to evaluate classification models.

    • Linear Regression is a regression model, not a classification model.

    • Evaluation metrics for Linear Regression include R-squared, Mean Squared Error, etc.

  • Answered by AI
  • Q7. 7. Explain KNN Algorithm?
  • Ans. 

    KNN is a non-parametric algorithm used for classification and regression tasks.

    • KNN stands for K-Nearest Neighbors.

    • It works by finding the K closest data points to a given test point.

    • The class or value of the test point is then determined by the majority class or average value of the K neighbors.

    • KNN can be used for both classification and regression tasks.

    • It is a simple and easy-to-understand algorithm, but can be compu

  • Answered by AI
  • Q8. 8. Explain Random Forest and Decision Tree?
  • Ans. 

    Random Forest is an ensemble learning method that builds multiple decision trees and combines their outputs to improve accuracy.

    • Random Forest is a type of supervised learning algorithm used for classification and regression tasks.

    • It creates multiple decision trees and combines their outputs to make a final prediction.

    • Each decision tree is built using a random subset of features and data points to reduce overfitting.

    • Ran...

  • Answered by AI
  • Q9. 9. One Tricky Mathematical Question !
  • Q10. 10. What are the Projects you have done?
  • Ans. 

    I have worked on various projects involving data analysis, machine learning, and predictive modeling.

    • Developed a predictive model to forecast customer churn for a telecommunications company.

    • Built a recommendation system using collaborative filtering for an e-commerce platform.

    • Performed sentiment analysis on social media data to understand customer opinions and preferences.

    • Implemented a fraud detection system using anom...

  • Answered by AI
  • Q11. I didn't get shortlisted for 2nd Round.

Interview Preparation Tips

General Tips: anyone who wants to go in data science field should actually be interested in the field not the money. They should be good in Statistics, Probability and Theory part of ML algorithms.
They will ask you about the projects you have mentioned in resume and all the questions will be from that part.
Skills: Communication, Body Language, Problem Solving, Analytical Skills
Duration: 1-4 weeks

Skills evaluated in this interview

Data Scientist Interview Questions & Answers

C5i user image Kushal Kulkarni

posted on 18 Jun 2024

Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I appeared for an interview in May 2024.

Round 1 - Assignment 

Questions based on ML,PYTHON, DATA VISUALIZATION

Round 2 - Technical 

(2 Questions)

  • Q1. What is TF-IDF IN NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document

    • TF-IDF is calculated by multiplying the term frequency (TF) by the inverse document frequency (IDF)

    • It helps in identifying the most important

  • Answered by AI
  • Q2. Python coding questions based on list

Interview Preparation Tips

Interview preparation tips for other job seekers - Practice python
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed before Dec 2023. There were 3 interview rounds.

Round 1 - Coding Test 

Test of Basic data structures in Python include lists, tuples, and dictionaries, as well as loops and conditional statements.

Round 2 - Case Study 

Framework and requirements for chatbot implementation.

Round 3 - HR 

(1 Question)

  • Q1. Salary discussion
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Assignment 

ML,DL,Python,NLP,Data VIsualization

Round 2 - Technical 

(1 Question)

  • Q1. Explain TF-IDF in NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency.

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document.

    • TF-IDF is calculated by multiplying the term frequency (TF) of a word by the inverse document frequency (IDF) of the word.

    • It helps in ident...

  • Answered by AI

Quantium Analytics Interview FAQs

How many rounds are there in Quantium Analytics interview?
Quantium Analytics interview process usually has 2-3 rounds. The most common rounds in the Quantium Analytics interview process are One-on-one Round, Aptitude Test and HR.
How to prepare for Quantium Analytics interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Quantium Analytics. The most common topics and skills that interviewers at Quantium Analytics expect are SQL, Python, Analytics, Consulting and Data Analytics.
What are the top questions asked in Quantium Analytics interview?

Some of the top questions asked at the Quantium Analytics interview -

  1. Are you aware Application Serv...read more
  2. explaon bigquery architectur...read more
  3. explain kubernetes on GK...read more

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Quantium Analytics Interview Process

based on 5 interviews

Interview experience

3.8
  
Good
View more

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Quantium Analytics Reviews and Ratings

based on 37 reviews

3.8/5

Rating in categories

3.2

Skill development

4.1

Work-life balance

4.0

Salary

3.9

Job security

4.1

Company culture

3.3

Promotions

3.4

Work satisfaction

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