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Klaim.ai Data Scientist 2 Interview Questions and Answers

Updated 12 Apr 2022

Klaim.ai Data Scientist 2 Interview Experiences

1 interview found

I applied via LinkedIn and was interviewed before Apr 2021. There were 3 interview rounds.

Round 1 - Case Study 

Focus on Healthtech

Round 2 - Coding Test 

Data science and deep learning

Round 3 - HR 

(1 Question)

  • Q1. What are your salary expectations?

Interview Preparation Tips

Interview preparation tips for other job seekers - Keep working on data science and engineering skills

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(3 Questions)

  • Q1. Difference between bagging and boosting
  • Ans. 

    Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.

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

    • Boosting involves training multiple models sequentially, where each subsequent model c...

  • Answered by AI
  • Q2. Parameters of Decision Tree
  • Ans. 

    Parameters of a Decision Tree include max depth, min samples split, criterion, and splitter.

    • Max depth: maximum depth of the tree

    • Min samples split: minimum number of samples required to split an internal node

    • Criterion: function to measure the quality of a split (e.g. 'gini' or 'entropy')

    • Splitter: strategy used to choose the split at each node (e.g. 'best' or 'random')

  • Answered by AI
  • Q3. Explain any one of your project in detail
  • Ans. 

    Developed a predictive model to forecast customer churn in a telecom company

    • Collected and cleaned customer data including usage patterns and demographics

    • Used machine learning algorithms such as logistic regression and random forest to build the model

    • Evaluated model performance using metrics like accuracy, precision, and recall

    • Provided actionable insights to the company to reduce customer churn rate

  • Answered by AI

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I was interviewed in Oct 2024.

Round 1 - Technical 

(1 Question)

  • Q1. Project related questions from your CV
Round 2 - Technical 

(2 Questions)

  • Q1. Question on transformers
  • Q2. Comparison of transfer learning and fintuning.
  • Ans. 

    Transfer learning involves using pre-trained models on a different task, while fine-tuning involves further training a pre-trained model on a specific task.

    • Transfer learning uses knowledge gained from one task to improve learning on a different task.

    • Fine-tuning involves adjusting the parameters of a pre-trained model to better fit a specific task.

    • Transfer learning is faster and requires less data compared to training a...

  • Answered by AI

Skills evaluated in this interview

Interview experience
2
Poor
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
No response

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

Round 1 - Technical 

(2 Questions)

  • Q1. SQL and pandas coding
  • Q2. Resume projects deep dive

Interview Preparation Tips

Interview preparation tips for other job seekers - No matter what kinds of questions indicated in HR email, be prepared for behavioral questions all the time
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - Coding Test 

*****, arjumpudi satyanarayana

Round 2 - Technical 

(5 Questions)

  • Q1. What is the python language
  • Ans. 

    Python is a high-level programming language known for its simplicity and readability.

    • Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.

    • It emphasizes code readability and uses indentation for block delimiters.

    • Python has a large standard library and a vibrant community of developers.

    • Example: print('Hello, World!')

    • Example: import pandas as pd

  • Answered by AI
  • Q2. What is the code problems
  • Ans. 

    Code problems refer to issues or errors in the code that need to be identified and fixed.

    • Code problems can include syntax errors, logical errors, or performance issues.

    • Examples of code problems include missing semicolons, incorrect variable assignments, or inefficient algorithms.

    • Identifying and resolving code problems is a key skill for data scientists to ensure accurate and efficient data analysis.

  • Answered by AI
  • Q3. What is the python code
  • Ans. 

    Python code is a programming language used for data analysis, machine learning, and scientific computing.

    • Python code is written in a text editor or an integrated development environment (IDE)

    • Python code is executed using a Python interpreter

    • Python code can be used for data manipulation, visualization, and modeling

  • Answered by AI
  • Q4. What is the project
  • Ans. 

    The project is a machine learning model to predict customer churn for a telecommunications company.

    • Developing predictive models using machine learning algorithms

    • Analyzing customer data to identify patterns and trends

    • Evaluating model performance and making recommendations for reducing customer churn

  • Answered by AI
  • Q5. What is the lnderssip
  • Ans. 

    The question seems to be incomplete or misspelled.

    • It is possible that the interviewer made a mistake while asking the question.

    • Ask for clarification or context to provide a relevant answer.

  • Answered by AI

Interview Preparation Tips

Topics to prepare for IBM Data Scientist interview:
  • Python
  • Machine Learning
Interview preparation tips for other job seekers - No

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Approached by Company and was interviewed in Sep 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Gave one easy question and asked what will be the output
  • Q2. Leetcode 2 sum question

Interview Preparation Tips

Interview preparation tips for other job seekers - I was pretty much sure that I would pass L1 round and hoping for L2 round. I was interviewing for Generative AI Engineer. It was full 1 hr. The interviewer was less experienced than me. He asked me about my current work and focused more on previous work. I gave 80% correct answers and still did not make it. Don't know what they were expecting from me. Then I thought, maybe they are just taking the interview for the name sake. Sometimes, rejections are baseless.
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Sep 2024. There were 2 interview rounds.

Round 1 - Technical 

(3 Questions)

  • Q1. Overfitting and Underfitting
  • Q2. Find Nth-largest element
  • Ans. 

    Find Nth-largest element in an array

    • Sort the array in descending order

    • Return the element at index N-1

  • Answered by AI
  • Q3. NLP Data preprocessing
Round 2 - HR 

(2 Questions)

  • Q1. Salary Discussion
  • Q2. Fitment discussion

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
-
Result
No response

I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.

Round 1 - Technical 

(6 Questions)

  • Q1. Which GenAI projects I have worked on
  • Q2. What is the context window in LLMs
  • Ans. 

    Context window in LLMs refers to the number of surrounding words considered when predicting the next word in a sequence.

    • Context window helps LLMs capture dependencies between words in a sentence.

    • A larger context window allows the model to consider more context but may lead to increased computational complexity.

    • For example, in a context window of 2, the model considers 2 words before and 2 words after the target word fo

  • Answered by AI
  • Q3. What is top_k parameter
  • Ans. 

    top_k parameter is used to specify the number of top elements to be returned in a result set.

    • top_k parameter is commonly used in machine learning algorithms to limit the number of predictions or recommendations.

    • For example, in recommendation systems, setting top_k=5 will return the top 5 recommended items for a user.

    • In natural language processing tasks, top_k can be used to limit the number of possible next words in a

  • Answered by AI
  • Q4. What are regex patterns in python
  • Ans. 

    Regex patterns in Python are sequences of characters that define a search pattern.

    • Regex patterns are used for pattern matching and searching in strings.

    • They are created using the 're' module in Python.

    • Examples of regex patterns include searching for email addresses, phone numbers, or specific words in a text.

  • Answered by AI
  • Q5. What are iterators and tuples
  • Ans. 

    Iterators are objects that allow iteration over a sequence of elements. Tuples are immutable sequences of elements.

    • Iterators are used to loop through elements in a collection, like lists or dictionaries

    • Tuples are similar to lists but are immutable, meaning their elements cannot be changed

    • Example of iterator: for item in list: print(item)

    • Example of tuple: my_tuple = (1, 2, 3)

  • Answered by AI
  • Q6. Do I have REST API experience
  • Ans. 

    Yes, I have experience working with REST APIs in various projects.

    • Developed RESTful APIs using Python Flask framework

    • Consumed REST APIs in data analysis projects using requests library

    • Used Postman for testing and debugging REST APIs

  • Answered by AI

Skills evaluated in this interview

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

I applied via campus placement at Indian Institute of Technology (IIT), Mandi and was interviewed before Jan 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. What factors should be considered when cleaning data?
  • Q2. Why was this particular project chosen
Interview experience
4
Good
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Recruitment Consulltant and was interviewed in Jul 2024. There were 3 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Deep questions about Machine learning, Deep learning, Generative AI, the working of transformers etc.
Round 2 - Technical 

(1 Question)

  • Q1. Deep questions about Machine learning and deep learning with projects done. This was a client round.
Round 3 - HR 

(1 Question)

  • Q1. Salary discussion, project discussion, why change? Why Wipro

Klaim.ai Interview FAQs

How many rounds are there in Klaim.ai Data Scientist 2 interview?
Klaim.ai interview process usually has 3 rounds. The most common rounds in the Klaim.ai interview process are Case Study, Coding Test and HR.

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