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Itobuz Technologies Principal Data Scientist Interview Questions, Process, and Tips

Updated 21 Mar 2023

Itobuz Technologies Principal Data Scientist Interview Experiences

1 interview found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Sep 2022. There were 4 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Technical 

(3 Questions)

  • Q1. Share your most recent project description and how you reach to the solution to it ?
  • Ans. 

    Developed a machine learning model to predict customer churn in a telecommunications company.

    • Collected and preprocessed customer data including demographics, usage patterns, and service history.

    • Performed exploratory data analysis to identify key features and patterns.

    • Built and trained a classification model using a combination of logistic regression and random forest algorithms.

    • Evaluated the model's performance using m...

  • Answered by AI
  • Q2. Python coding related questions
  • Q3. Statistical problem related questions
Round 3 - One-on-one 

(14 Questions)

  • Q1. What all you know about Multivariate Analysis ?
  • Ans. 

    Multivariate analysis is a statistical technique used to analyze data with multiple variables.

    • It involves examining the relationships between multiple variables to identify patterns and trends.

    • Common techniques include principal component analysis, factor analysis, and cluster analysis.

    • Multivariate analysis is used in various fields such as finance, marketing, and social sciences.

    • Example: A marketing team may use multi...

  • Answered by AI
  • Q2. What is multivariate time series and how to model it ?
  • Ans. 

    Multivariate time series is a collection of time series data where multiple variables are observed simultaneously over time.

    • Multivariate time series models are used to analyze and forecast complex systems with multiple interacting variables.

    • Common models include Vector Autoregression (VAR), Vector Error Correction Model (VECM), and Dynamic Factor Models (DFM).

    • Model selection and parameter estimation can be challenging ...

  • Answered by AI
  • Q3. Is it always important to apply ML algorithms to solve any statistical problem?
  • Ans. 

    No, it is not always important to apply ML algorithms to solve any statistical problem.

    • ML algorithms may not be necessary for simple statistical problems

    • ML algorithms require large amounts of data and computing power

    • ML algorithms may not always provide the most interpretable results

    • Statistical models may be more appropriate for certain types of data

    • ML algorithms should be used when they provide a clear advantage over t

  • Answered by AI
  • Q4. What all you know about Anomaly detection?
  • Ans. 

    Anomaly detection is the process of identifying data points that deviate from the expected pattern.

    • Anomaly detection is used in various fields such as finance, cybersecurity, and manufacturing.

    • It can be done using statistical methods, machine learning algorithms, or a combination of both.

    • Some common techniques for anomaly detection include clustering, classification, and time series analysis.

    • Examples of anomalies inclu...

  • Answered by AI
  • Q5. Do you know about Event Detection?
  • Ans. 

    Event Detection is the process of identifying and extracting meaningful events from data streams.

    • It involves analyzing data in real-time to detect patterns and anomalies

    • It is commonly used in fields such as finance, social media, and security

    • Examples include detecting fraudulent transactions, identifying trending topics on Twitter, and detecting network intrusions

  • Answered by AI
  • Q6. Have you heard about Gaussian Mixture Model? Can you explain it with an proper industrial example?
  • Ans. 

    Gaussian Mixture Model is a probabilistic model used for clustering and density estimation.

    • GMM assumes that the data points are generated from a mixture of Gaussian distributions.

    • It estimates the parameters of these Gaussian distributions to cluster the data points.

    • An industrial example of GMM is in customer segmentation for targeted marketing.

    • GMM can also be used in anomaly detection and image segmentation.

  • Answered by AI
  • Q7. How can you use GMM in anomaly detection?
  • Ans. 

    GMM can be used to model normal behavior and identify anomalies based on low probability density.

    • GMM can be used to fit a model to the normal behavior of a system or process.

    • Anomalies can be identified as data points with low probability density under the GMM model.

    • The number of components in the GMM can be adjusted to balance between overfitting and underfitting.

    • GMM can be combined with other techniques such as PCA or...

  • Answered by AI
  • Q8. Which one is more robust for Anomaly detection? Tukey's method of IQR or Z-Score method or GMM ?
  • Ans. 

    GMM is more robust for Anomaly detection than Tukey's method of IQR or Z-Score method.

    • GMM can handle complex data distributions and can identify multiple anomalies.

    • Tukey's method and Z-Score method are limited to detecting anomalies in unimodal distributions.

    • GMM can also handle missing data points and outliers better than the other two methods.

  • Answered by AI
  • Q9. What makes GMM robust to the Anomaly detection?
  • Ans. 

    GMM is robust to anomaly detection due to its ability to model complex data distributions.

    • GMM can model data distributions with multiple modes, making it more flexible than other methods.

    • It can also handle data with varying densities and shapes, making it suitable for detecting anomalies.

    • GMM uses a probabilistic approach to assign data points to different clusters, allowing it to identify outliers.

    • It can be used in uns...

  • Answered by AI
  • Q10. How to detect anomalies in Multivariate Time Series ?
  • Ans. 

    Anomalies in Multivariate Time Series can be detected using statistical methods like PCA, clustering, and deep learning models.

    • Use Principal Component Analysis (PCA) to identify the most important features and detect anomalies in the residual errors.

    • Cluster the data points and identify the clusters with low density or high variance as anomalies.

    • Use deep learning models like LSTM or Autoencoder to learn the patterns in ...

  • Answered by AI
  • Q11. What is more robust to outliers? Mean, median or mode ?
  • Ans. 

    Median is more robust to outliers than mean and mode.

    • Mean is sensitive to outliers as it takes into account all the values in the dataset.

    • Mode is not affected by outliers as it only considers the most frequent value.

    • Median is the middle value in a dataset and is less affected by outliers as it is not influenced by extreme values.

    • For example, if we have a dataset of salaries and one person earns a million dollars, the m...

  • Answered by AI
  • Q12. What is Mahalanobis Distance? Can you illustrate it's assumptions ?
  • Ans. 

    Mahalanobis Distance is a measure of distance between a point and a distribution.

    • It takes into account the covariance between variables.

    • It is used in multivariate analysis and classification problems.

    • Assumes that the data is normally distributed and has equal covariance matrices.

    • It is sensitive to outliers and can be used to detect them.

  • Answered by AI
  • Q13. What is the difference between Euclidean distance and Mahalanobis Distance?
  • Ans. 

    Euclidean distance measures straight line distance between two points while Mahalanobis distance considers variance and covariance of the data.

    • Euclidean distance is the most common distance metric used in machine learning.

    • Mahalanobis distance is used when the data has different variances and covariances.

    • Mahalanobis distance is more robust to outliers than Euclidean distance.

    • Mahalanobis distance is used in clustering, c...

  • Answered by AI
  • Q14. Do you know any Anomaly detection method that will work without Normality Assumptions?
  • Ans. 

    Yes, Local Outlier Factor (LOF) is a non-parametric anomaly detection method that does not require normality assumptions.

    • LOF is based on the idea that anomalies are located in less dense areas than their neighbors

    • LOF calculates the local density of each data point and compares it to the densities of its neighbors

    • LOF assigns an anomaly score to each data point based on how much its local density differs from the densiti

  • Answered by AI
Round 4 - HR 

(4 Questions)

  • Q1. Describe yourself in 3 word ?
  • Ans. 

    Analytical, innovative, detail-oriented

    • Analytical: I have a strong ability to analyze complex data and extract meaningful insights.

    • Innovative: I constantly seek new and creative approaches to problem-solving and developing data-driven solutions.

    • Detail-oriented: I pay close attention to details to ensure accuracy and precision in my work.

  • Answered by AI
  • Q2. What's your hobby and why ?
  • Ans. 

    My hobby is photography because it allows me to capture and express the beauty of the world.

    • Photography allows me to explore and appreciate the details in my surroundings.

    • It helps me to see things from different perspectives and enhances my creativity.

    • I enjoy experimenting with different techniques and capturing unique moments.

    • Photography also serves as a form of relaxation and mindfulness for me.

  • Answered by AI
  • Q3. How do you score yourself in interpersonal skills and why ?
  • Ans. 

    I score myself highly in interpersonal skills because I have a proven track record of effectively communicating and collaborating with diverse teams.

    • I have excellent communication skills, both verbal and written.

    • I am able to listen actively and empathetically to others.

    • I can effectively convey complex technical concepts to non-technical stakeholders.

    • I have experience working in cross-functional teams and fostering posi...

  • Answered by AI
  • Q4. Tell me why do you think you're fit for this role ?
  • Ans. 

    I have a strong background in data science and leadership skills necessary for the role of Principal Data Scientist.

    • Extensive experience in data analysis and modeling

    • Proven track record of leading successful data science projects

    • Strong knowledge of machine learning algorithms and statistical techniques

    • Ability to communicate complex findings to both technical and non-technical stakeholders

    • Experience in managing and ment...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare yourself with good knowledge of python, latest technologies introducing in Data Science and have good knowledge of Statistics. Questions are common but they'll ask for explanation in every single step.

Skills evaluated in this interview

Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. Questions related to COBOL,JCL,VSAM,DB2,CICS,Vision plus

Interview Questionnaire 

7 Questions

  • Q1. Solid principles
  • Q2. Extension methods
  • Q3. Static class and static constructor
  • Ans. 

    Static class and static constructor in C#

    • Static class can only contain static members and cannot be instantiated

    • Static constructor is called only once when the class is first accessed

    • Static constructor is used to initialize static members of the class

    • Example: Math class in C# is a static class

    • Example: static constructor can be used to initialize a static variable with a value

  • Answered by AI
  • Q4. Polymorphism
  • Q5. Dependency injection
  • Q6. Angular life cycle hook
  • Q7. Performance improvement in Angular app
  • Ans. 

    Performance improvement in Angular app

    • Use lazy loading to load modules on demand

    • Optimize change detection strategy

    • Use trackBy function in ngFor loops

    • Minimize DOM manipulation

    • Use AOT compilation

    • Implement server-side rendering

    • Use web workers for heavy computations

    • Use caching for frequently accessed data

  • Answered by AI

Skills evaluated in this interview

Interview Questionnaire 

1 Question

  • Q1. From start to end how you perform web application penetration testing on a website with firewall is enabled on it?
  • Ans. 

    Performing web application penetration testing on a website with firewall enabled.

    • Identify the type of firewall and its configuration

    • Perform reconnaissance to gather information about the target

    • Identify vulnerabilities and exploit them

    • Use tools like Burp Suite, Nmap, and Metasploit

    • Test for common web application vulnerabilities like SQL injection and cross-site scripting

    • Document findings and provide recommendations for

  • Answered by AI

Skills evaluated in this interview

I appeared for an interview before Dec 2020.

Round 1 - Coding Test 

(1 Question)

Round duration - 120 Minutes
Round difficulty - Medium

  • Q1. 

    Ninja and His Secret Information Encoding Problem

    Ninja, a new member of the FBI, has acquired some 'SECRET_INFORMATION' that he needs to share with his team. To ensure security against hackers, Ninja dec...

  • Ans. 

    The task is to encode and decode 'SECRET_INFORMATION' for security purposes and determine if the transmission was successful.

    • Read the number of test cases 'T'

    • For each test case, encode the 'SECRET_INFORMATION' and then decode it

    • Compare the decoded string with the original 'SECRET_INFORMATION'

    • Print 'Transmission successful' if they match, else print 'Transmission failed'

  • Answered by AI
Round 2 - Face to Face 

(1 Question)

Round duration - 60 Minutes
Round difficulty - Medium

  • Q1. 

    Equilibrium Index Problem Statement

    Given an array Arr consisting of N integers, your task is to find the equilibrium index of the array.

    An index is considered as an equilibrium index if the sum of elem...

  • Ans. 

    Find the equilibrium index of an array where sum of elements on left equals sum on right.

    • Iterate through the array and calculate prefix sum and suffix sum at each index.

    • Compare prefix sum and suffix sum to find equilibrium index.

    • Return the left-most equilibrium index or -1 if none found.

  • Answered by AI
Round 3 - HR 

Round duration - 50 Minutes
Round difficulty - Easy

Interview Preparation Tips

Professional and academic backgroundI applied for the job as Data Analyst in PuneEligibility criteria7 CGPACapgemini interview preparation:Topics to prepare for the interview - Data Structures, OOPS, SQL, Python, JavaTime required to prepare for the interview - 1 MonthInterview preparation tips for other job seekers

Tip 1 : Focus more on SQL
Tip 2 : Keep up with ongoing projects in the company

Application resume tips for other job seekers

Tip 1 : Be honest about what you add.
Tip 2 : Don't forget to mention extra curriculars.

Final outcome of the interviewSelected

Skills evaluated in this interview

I applied via Naukri.com and was interviewed in Jan 2021. There were 4 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Mostly the technical question from my skill background. As the interview was in video conference mode so mostly conceptual and very few coding and query related problem solving question has been asked.

Interview Preparation Tips

Interview preparation tips for other job seekers - 1. Be aware of your resume very well
2. Don't falsify your skill set.
3. Make sure you have good concept and problem solving ability on your skill
set.
4. Be confident and clear about your answer. It is always a good practice if you
are trying to explain something give an example with it.
5. Best of Luck !!!!

I applied via Naukri.com and was interviewed in Jan 2021. There was 1 interview round.

Interview Questionnaire 

1 Question

  • Q1. Azure migration steps from onprem to cloud, Hyper V migration, VMWARE tool we used for migration
  • Ans. 

    Steps for Azure migration from onprem to cloud and Hyper V migration using VMWARE tool.

    • Assess on-premises environment

    • Choose appropriate migration method

    • Prepare Azure environment

    • Migrate data and applications

    • Optimize and secure migrated resources

    • VMware tool used for migration: VMware vCenter Converter

    • Hyper-V migration can be done using Azure Site Recovery

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Just understand the process, recent issues we handled and fixed with what role we involved to fix the issue,

Skills evaluated in this interview

I applied via Naukri.com and was interviewed in Mar 2021. There were 4 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Memory management in applications
  • Ans. 

    Memory management is crucial for efficient application performance.

    • Memory allocation and deallocation should be done carefully to avoid memory leaks.

    • Unused memory should be released to prevent memory fragmentation.

    • Memory profiling tools can help identify memory-related issues.

    • Caching can improve performance by reducing the need for frequent memory allocation.

    • Examples: Java's garbage collector, C++'s smart pointers, iOS

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - On date of interview, be calm and be online before time.
Try to answer an much you can.
Normally questions are related to respective technology.
So if you have good knowledge on your technology then you can crack it.
After you clear 1st round then there will be AMCAT round. After completion you there will be a hr round.

I applied via Naukri.com and was interviewed in Jul 2021. There were 3 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Resume questions only

Interview Preparation Tips

Interview preparation tips for other job seekers - Please brush up your skills.

I applied via Referral and was interviewed before Jan 2021. There were 3 interview rounds.

Interview Questionnaire 

2 Questions

  • Q1. Why u are applying for new job
  • Q2. Technical questions

Interview Preparation Tips

Interview preparation tips for other job seekers - Try to be confident, dont get nervous,
Speak what ever you know in technical terms.

Itobuz Technologies Interview FAQs

How many rounds are there in Itobuz Technologies Principal Data Scientist interview?
Itobuz Technologies interview process usually has 4 rounds. The most common rounds in the Itobuz Technologies interview process are Technical, One-on-one Round and HR.
How to prepare for Itobuz Technologies Principal Data Scientist 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 Itobuz Technologies . The most common topics and skills that interviewers at Itobuz Technologies expect are Artificial Intelligence, Data Science, Machine Learning, Pattern Recognition and Python.
What are the top questions asked in Itobuz Technologies Principal Data Scientist interview?

Some of the top questions asked at the Itobuz Technologies Principal Data Scientist interview -

  1. Is it always important to apply ML algorithms to solve any statistical probl...read more
  2. What is multivariate time series and how to model i...read more
  3. Do you know any Anomaly detection method that will work without Normality Assum...read more

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Itobuz Technologies Principal Data Scientist Interview Process

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