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Fragma Data Systems Data Scientist Interview Questions and Answers

Updated 17 Jun 2021

Fragma Data Systems Data Scientist Interview Experiences

1 interview found

I applied via Company Website and was interviewed before Jun 2020. There was 1 interview round.

Interview Questionnaire 

1 Question

  • Q1. Brief about your college project

Interview Preparation Tips

Interview preparation tips for other job seekers - 3 Rounds were there for the freshers one online exam they call after a week if you cleared the test for the next round, one technical round during this they asked project that you worked on, some questions on job related

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Interview experience
1
Bad
Difficulty level
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Process Duration
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Result
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Round 1 - Coding Test 

SQL AND POWERBI related questions

Interview Preparation Tips

Interview preparation tips for other job seekers - These guys are just wasting time. They shortlisted my profile based on my resume, but after I performed well in the interview, they rejected me, saying they need more experience than what was originally mentioned. They're giving invalid feedback just for the sake of it. Please don’t waste your time on this kind of company.

I applied via LinkedIn and was interviewed in Sep 2020. There were 5 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Explain VIF
  • Ans. 

    VIF stands for Variance Inflation Factor, a measure of multicollinearity in regression analysis.

    • VIF is used to detect the presence of multicollinearity in regression analysis.

    • It measures how much the variance of the estimated regression coefficient is increased due to multicollinearity.

    • A VIF value of 1 indicates no multicollinearity, while a value greater than 1 suggests increasing levels of multicollinearity.

    • A commonl...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Focus on the projects that has been done in past

I applied via Walk-in and was interviewed in Mar 2020. There was 1 interview round.

Interview Questionnaire 

10 Questions

  • Q1. What is R square and how R square is different from Adjusted R square
  • Ans. 

    R square is a statistical measure that represents the proportion of the variance in the dependent variable explained by the independent variables.

    • R square is a value between 0 and 1, where 0 indicates that the independent variables do not explain any of the variance in the dependent variable, and 1 indicates that they explain all of it.

    • It is used to evaluate the goodness of fit of a regression model.

    • Adjusted R square t...

  • Answered by AI
  • Q2. Explain what do u understand by the team WOE and IV. What's the importance. Advantages and disadvantages
  • Q3. What are variable reducing techniques
  • Ans. 

    Variable reducing techniques are methods used to identify and select the most relevant variables in a dataset.

    • Variable reducing techniques help in reducing the number of variables in a dataset.

    • These techniques aim to identify the most important variables that contribute significantly to the outcome.

    • Some common variable reducing techniques include feature selection, dimensionality reduction, and correlation analysis.

    • Fea...

  • Answered by AI
  • Q4. Which test is used in logistic regression to check the significance of the variable
  • Ans. 

    The Wald test is used in logistic regression to check the significance of the variable.

    • The Wald test calculates the ratio of the estimated coefficient to its standard error.

    • It follows a chi-square distribution with one degree of freedom.

    • A small p-value indicates that the variable is significant.

    • For example, in Python, the statsmodels library provides the Wald test in the summary of a logistic regression model.

  • Answered by AI
  • Q5. How to check multicollinearity in Logistic regression
  • Ans. 

    Multicollinearity in logistic regression can be checked using correlation matrix and variance inflation factor (VIF).

    • Calculate the correlation matrix of the independent variables and check for high correlation coefficients.

    • Calculate the VIF for each independent variable and check for values greater than 5 or 10.

    • Consider removing one of the highly correlated variables or variables with high VIF to address multicollinear...

  • Answered by AI
  • Q6. Difference between bagging and boosting
  • Ans. 

    Bagging and boosting are ensemble methods used in machine learning to improve model performance.

    • Bagging involves training multiple models on different subsets of the training data and then combining their predictions through averaging or voting.

    • Boosting involves iteratively training models on the same dataset, with each subsequent model focusing on the samples that were misclassified by the previous model.

    • Bagging reduc...

  • Answered by AI
  • Q7. Explain the logistics regression process
  • Ans. 

    Logistic regression is a statistical method used to analyze and model the relationship between a binary dependent variable and one or more independent variables.

    • It is a type of regression analysis used for predicting the outcome of a categorical dependent variable based on one or more predictor variables.

    • It uses a logistic function to model the probability of the dependent variable taking a particular value.

    • It is commo...

  • Answered by AI
  • Q8. Explain Gini coefficient
  • Ans. 

    Gini coefficient measures the inequality among values of a frequency distribution.

    • Gini coefficient ranges from 0 to 1, where 0 represents perfect equality and 1 represents perfect inequality.

    • It is commonly used to measure income inequality in a population.

    • A Gini coefficient of 0.4 or higher is considered to be a high level of inequality.

    • Gini coefficient can be calculated using the Lorenz curve, which plots the cumulati...

  • Answered by AI
  • Q9. Difference between chair and cart
  • Ans. 

    A chair is a piece of furniture used for sitting, while a cart is a vehicle used for transporting goods.

    • A chair typically has a backrest and armrests, while a cart does not.

    • A chair is designed for one person to sit on, while a cart can carry multiple items or people.

    • A chair is usually stationary, while a cart is mobile and can be pushed or pulled.

    • A chair is commonly found in homes, offices, and public spaces, while a c...

  • Answered by AI
  • Q10. How to check outliers in a variable, what treatment should you use to remove such outliers
  • Ans. 

    Outliers can be detected using statistical methods like box plots, z-score, and IQR. Treatment can be removal or transformation.

    • Use box plots to visualize outliers

    • Calculate z-score and remove data points with z-score greater than 3

    • Calculate IQR and remove data points outside 1.5*IQR

    • Transform data using log or square root to reduce the impact of outliers

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Explain the concept properly, if not able to explain properly then take a pause and try again with some examples. Be confident.

Skills evaluated in this interview

I applied via Campus Placement and was interviewed in Dec 2020. There were 3 interview rounds.

Interview Questionnaire 

2 Questions

  • Q1. Tell me about yourself Why data science Tell me about regression Evaluation metrics
  • Q2. What is accuracy What is precision
  • Ans. 

    Accuracy is the closeness of a measured value to the true value. Precision is the consistency of repeated measurements.

    • Accuracy measures how close a measurement is to the true value

    • Precision measures the consistency of repeated measurements

    • Accuracy can be affected by systematic errors

    • Precision can be affected by random errors

    • Accuracy and precision are both important in scientific measurements

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Just keep basics concepts clear

Skills evaluated in this interview

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

Interview Questionnaire 

2 Questions

  • Q1. What is data science
  • Ans. 

    Data science is the field of extracting insights and knowledge from data using various techniques and tools.

    • Data science involves collecting, cleaning, and analyzing data to extract insights.

    • It uses various techniques such as machine learning, statistical modeling, and data visualization.

    • Data science is used in various fields such as finance, healthcare, and marketing.

    • Examples of data science applications include fraud...

  • Answered by AI
  • Q2. What is phyton and R
  • Ans. 

    Python and R are programming languages commonly used in data science and statistical analysis.

    • Python is a general-purpose language with a large community and many libraries for data manipulation and machine learning.

    • R is a language specifically designed for statistical computing and graphics, with a wide range of packages for data analysis and visualization.

    • Both languages are popular choices for data scientists and hav...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Provide the tips how to face the interview

Skills evaluated in this interview

Interview Questionnaire 

2 Questions

  • Q1. Three skills required to be a good data scientist?
  • Q2. Answer: Curious , Extremely argumentative and judgemental

I applied via Approached by Company and was interviewed before Sep 2021. There were 3 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 

(1 Question)

  • Q1. Projects and Data Science concepts
Round 3 - Technical 

(1 Question)

  • Q1. Python and coding skills

Interview Preparation Tips

Interview preparation tips for other job seekers - Be through with concepts - ML, stats, NLP

I applied via Approached by Company and was interviewed before Sep 2021. There were 3 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Don’t add your photo or details such as gender, age, and address in your resume. These details do not add any value.
View all tips
Round 2 - Aptitude Test 

Explain dynamic programming with memoization

Round 3 - HR 

(2 Questions)

  • Q1. Where are you from, and why are you joining the company
  • Q2. Why are you joining the company

Interview Preparation Tips

Interview preparation tips for other job seekers - First, they will ask about the breadth of your ML skills and the depth going forward

I applied via Job Portal and was interviewed in Jan 2021. There were 3 interview rounds.

Interview Questionnaire 

2 Questions

  • Q1. Basic Hypothesis Understanding !
  • Q2. Apache Spark and Data Frames

Interview Preparation Tips

Interview preparation tips for other job seekers - Ask clearly for job role they said data scientist but currently I am doing MLOPS

Fragma Data Systems Interview FAQs

How to prepare for Fragma Data Systems 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 Fragma Data Systems. The most common topics and skills that interviewers at Fragma Data Systems expect are Machine Learning, Python, Artificial Intelligence, Data Science and SQL.

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Fragma Data Systems Data Scientist Salary
based on 11 salaries
₹5.4 L/yr - ₹18 L/yr
19% less than the average Data Scientist Salary in India
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Fragma Data Systems Data Scientist Reviews and Ratings

based on 11 reviews

4.7/5

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5.0

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4.7

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5.0

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4.9

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4.9

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5.0

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5.0

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