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EdgeVerve Systems Data Scientist Interview Questions and Answers

Updated 28 May 2024

EdgeVerve Systems Data Scientist Interview Experiences

1 interview found

Interview experience
3
Average
Difficulty level
-
Process Duration
4-6 weeks
Result
No response

I appeared for an interview before May 2023.

Round 1 - Technical 

(1 Question)

  • Q1. Coding round hackerrank
Round 2 - Technical 

(1 Question)

  • Q1. Around fundamentals of mL

Data Scientist Jobs at EdgeVerve Systems

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Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Nov 2024. There were 3 interview rounds.

Round 1 - HR 

(1 Question)

  • Q1. Basicn details to check for qualifications
Round 2 - Technical 

(1 Question)

  • Q1. About my projects
Round 3 - Technical 

(1 Question)

  • Q1. More details about ML models
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Asked about some machine learning concepts like NLP, TensorFlow etc
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Referral and was interviewed in Aug 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Explain Feature selection Techniques
  • Ans. 

    Feature selection techniques are methods used to select the most relevant features for a predictive model.

    • Filter methods: Select features based on statistical measures like correlation, chi-squared, or mutual information.

    • Wrapper methods: Use a specific model to evaluate the importance of features by training and testing subsets of features.

    • Embedded methods: Features are selected as part of the model training process, l...

  • Answered by AI
  • Q2. Difference between Covariance and Correlation
  • Ans. 

    Covariance measures the relationship between two variables, while correlation measures the strength and direction of a relationship.

    • Covariance can be positive, negative, or zero, indicating the direction of the relationship.

    • Correlation is always between -1 and 1, with 1 indicating a perfect positive relationship, -1 indicating a perfect negative relationship, and 0 indicating no relationship.

    • Covariance is affected by t...

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(3 Questions)

  • Q1. About projects and then questions related to ML and DL. Mostly focused on DL part
  • Q2. What is the difference between Adam optimizer and Gradient Descent Optimizer?
  • Ans. 

    Adam optimizer is an extension to the Gradient Descent optimizer with adaptive learning rates and momentum.

    • Adam optimizer combines the benefits of both AdaGrad and RMSProp optimizers.

    • Adam optimizer uses adaptive learning rates for each parameter.

    • Gradient Descent optimizer has a fixed learning rate for all parameters.

    • Adam optimizer includes momentum to speed up convergence.

    • Gradient Descent optimizer updates parameters b...

  • Answered by AI
  • Q3. When to use Relu and when not?
  • Ans. 

    Use ReLU for hidden layers in deep neural networks, avoid for output layers.

    • ReLU is commonly used in hidden layers to introduce non-linearity and speed up convergence.

    • Avoid using ReLU in output layers for regression tasks as it can lead to vanishing gradients.

    • Consider using Leaky ReLU or Sigmoid for output layers depending on the task.

    • ReLU is computationally efficient and helps in preventing the vanishing gradient prob...

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Not Selected

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

Round 1 - Coding Test 

Standard question from sql and python in hackerrank

Round 2 - Technical 

(2 Questions)

  • Q1. Reverse a linked list
  • Ans. 

    Reverse a linked list by changing the direction of pointers

    • Start with three pointers: current, previous, and next

    • Iterate through the linked list, updating pointers to reverse the direction

    • Return the new head of the reversed linked list

  • Answered by AI
  • Q2. Question based on joins and subquery
Round 3 - HR 

(2 Questions)

  • Q1. More question about project
  • Q2. What do you know about genAI

Interview Preparation Tips

Interview preparation tips for other job seekers - Keep it simple and be honest

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via Referral and was interviewed before May 2023. There were 4 interview rounds.

Round 1 - Aptitude Test 

180 mins of online test with camera ON. Major topics include Excel, Aptitude, Python, Statistics and Case Study

Round 2 - Technical 

(2 Questions)

  • Q1. Explain Apriori Method
  • Ans. 

    Apriori method is a popular algorithm for frequent itemset mining in data mining.

    • Used for finding frequent itemsets in transactional databases

    • Based on the concept of association rule mining

    • Involves generating candidate itemsets and pruning based on support threshold

    • Example: If {milk, bread} is a frequent itemset, then {milk} and {bread} are also frequent

  • Answered by AI
  • Q2. Explain train-test in Scikit learn
  • Ans. 

    Train-test split is a method used to divide a dataset into training and testing sets for model evaluation in Scikit learn.

    • Split the dataset into two subsets: training set and testing set

    • Training set is used to train the model, while testing set is used to evaluate the model's performance

    • Common split ratios are 70-30 or 80-20 for training and testing sets

    • Example: X_train, X_test, y_train, y_test = train_test_split(X, y,

  • Answered by AI
Round 3 - One-on-one 

(2 Questions)

  • Q1. Explain about projects in current company
  • Q2. Why do you want to move to an individual contributor role from a managerial position
Round 4 - One-on-one 

(2 Questions)

  • Q1. Why do you want to join Wolters Kluwer?
  • Q2. Discussion around analytics and managerment reporting deliverables in current org.

Interview Preparation Tips

Topics to prepare for Wolters Kluwer Data Scientist interview:
  • Advanced Excel
  • Python
  • Power Bi
  • Pivot Table
Interview preparation tips for other job seekers - You must be an advanced Excel user and decent knowledge of Python.

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(1 Question)

  • Q1. Tell me about your self

Interview Preparation Tips

Round: Interview
Experience: They asked to write 2 codes on recursion. Then some questions on resume. I asked them about the job profile and after knowing that they were hiring candidates for frontend programming, about which they didn’t mention in JAF. I told them that I was not interested in frontend development. And didn’t even answer any question after that. Unfortunately, I was selected.

General Tips: Plan your schedule judiciously keeping your capacity in mind. There is no point of making ideal plans and then not able to do even 50% of it.
Don’t get into unnecessary arguments or debate with people.
Don’t think about what others are doing. Focus on your preparation.
How you carry yourself matters. So, make sure you portray yourself in the way you want the other person to perceive you.
Be selective while applying for companies.
College Name: IIT Kanpur

Interview Questionnaire 

3 Questions

  • Q1. How will you optimize ticket closing process
  • Ans. 

    I will streamline the process by identifying bottlenecks and implementing automation.

    • Analyze current process flow

    • Identify areas of delay or inefficiency

    • Implement automation tools to reduce manual effort

    • Set up clear communication channels between team members

    • Track progress and adjust as needed

  • Answered by AI
  • Q2. Explain what course of actions will be taken by you if your colleagues and manager don't co operate with you
  • Q3. Take any example in ticket closing and explain how will you do hypothesis testing
  • Ans. 

    Hypothesis testing in ticket closing example

    • Define null and alternative hypothesis

    • Choose appropriate statistical test

    • Set significance level

    • Collect data and calculate test statistic

    • Determine p-value and compare with significance level

    • Make conclusion and interpret results

  • Answered by AI

EdgeVerve Systems Interview FAQs

How many rounds are there in EdgeVerve Systems Data Scientist interview?
EdgeVerve Systems interview process usually has 2 rounds. The most common rounds in the EdgeVerve Systems interview process are Technical.
How to prepare for EdgeVerve 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 EdgeVerve Systems. The most common topics and skills that interviewers at EdgeVerve Systems expect are Python, Data Science, Machine Learning, Deep Learning and Artificial Intelligence.
What are the top questions asked in EdgeVerve Systems Data Scientist interview?

Some of the top questions asked at the EdgeVerve Systems Data Scientist interview -

  1. Coding round hackerr...read more
  2. Around fundamentals of...read more

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EdgeVerve Systems Data Scientist Interview Process

based on 1 interview

Interview experience

3
  
Average
View more
EdgeVerve Systems Data Scientist Salary
based on 16 salaries
₹7.3 L/yr - ₹21.1 L/yr
6% more than the average Data Scientist Salary in India
View more details

EdgeVerve Systems Data Scientist Reviews and Ratings

based on 1 review

4.0/5

Rating in categories

5.0

Skill development

5.0

Work-life balance

3.0

Salary

5.0

Job security

5.0

Company culture

5.0

Promotions

5.0

Work satisfaction

Explore 1 Review and Rating
Data Scientist

Chennai,

Bangalore / Bengaluru

8-13 Yrs

Not Disclosed

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