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ONLEI Technologies Data Science Intern Interview Questions and Answers

Updated 15 Jan 2025

ONLEI Technologies Data Science Intern Interview Experiences

2 interviews found

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

(2 Questions)

  • Q1. Hsjfbfthehfbf fauzia hii boo
  • Q2. Ndjf Ncjfhf fh

Interview Preparation Tips

Interview preparation tips for other job seekers - 1. Strengthen Your Skills

Programming: Master Python or R, as they're widely used in data science.

Statistics & Math: Understand core concepts like probability, linear algebra, and calculus.

Data Manipulation: Get comfortable with libraries like Pandas and NumPy.

Data Visualization: Learn tools like Matplotlib, Seaborn, or Tableau.

Machine Learning: Study algorithms using Scikit-learn or TensorFlow.


2. Build a Portfolio

Work on projects like:

Exploratory data analysis (EDA) of public datasets.

Predictive modeling (e.g., forecasting sales or stock prices).

Sentiment analysis on social media data.


Host your projects on GitHub or a personal website for visibility.


3. Create a Strong Resume

Highlight technical skills and tools you’ve mastered.

Showcase projects, internships, or certifications.

Mention soft skills like problem-solving and communication.
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-

I applied via Walk-in

Round 1 - Aptitude Test 

An aptitude test is an exam used to determine an individual's skill or propensity to succeed in a given activity.

Round 2 - Coding Test 

1 what is a data structure
2 what is an array
3 what is a linked list
4 what is LIFO
5 what is FIFO

Interview Preparation Tips

Interview preparation tips for other job seekers - Research Potential Employers
Network..
Develop and Showcase Relevant Skills

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

I applied via Campus Placement and was interviewed in Nov 2024. There were 3 interview rounds.

Round 1 - Aptitude Test 

There were verbal, non verbal, reasoning , English and maths questions

Round 2 - Technical 

(2 Questions)

  • Q1. Tell me about your project.
  • Ans. 

    I worked on a project analyzing customer behavior using machine learning algorithms.

    • Used Python for data preprocessing and analysis

    • Implemented machine learning models such as decision trees and logistic regression

    • Performed feature engineering to improve model performance

  • Answered by AI
  • Q2. What programming knowledge you have ?
  • Ans. 

    Proficient in Python, R, and SQL with experience in data manipulation, visualization, and machine learning algorithms.

    • Proficient in Python for data analysis and machine learning tasks

    • Experience with R for statistical analysis and visualization

    • Knowledge of SQL for querying databases and extracting data

    • Familiarity with libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn

  • Answered by AI
Round 3 - HR 

(2 Questions)

  • Q1. Where do you stay ?
  • Ans. 

    I currently stay in an apartment in downtown area.

    • I stay in an apartment in downtown area

    • My current residence is in a city

    • I live close to my workplace

  • Answered by AI
  • Q2. Tell me about you
  • Ans. 

    I am a data science enthusiast with a strong background in statistics and machine learning.

    • Background in statistics and machine learning

    • Passionate about data science

    • Experience with data analysis tools like Python and R

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
-
Result
-

I applied via Campus Placement

Round 1 - Technical 

(1 Question)

  • Q1. ML and deep learning questions
Round 2 - Interview 

(2 Questions)

  • Q1. Projects discussion
  • Q2. Chatgpt architecture
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Basic DSA questions will be asked Leetcode Easy to medium

Round 2 - Technical 

(2 Questions)

  • Q1. BERT vs LSTM and their speed
  • Ans. 

    BERT is faster than LSTM due to its transformer architecture and parallel processing capabilities.

    • BERT utilizes transformer architecture which allows for parallel processing of words in a sentence, making it faster than LSTM which processes words sequentially.

    • BERT has been shown to outperform LSTM in various natural language processing tasks due to its ability to capture long-range dependencies more effectively.

    • For exa...

  • Answered by AI
  • Q2. What is multinomial Naive Bayes theorem
  • Ans. 

    Multinomial Naive Bayes is a classification algorithm based on Bayes' theorem with the assumption of independence between features.

    • It is commonly used in text classification tasks, such as spam detection or sentiment analysis.

    • It is suitable for features that represent counts or frequencies, like word counts in text data.

    • It calculates the probability of each class given the input features and selects the class with the

  • Answered by AI

Skills evaluated in this interview

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

I applied via campus placement at Chennai Mathematical Institute, Chennai and was interviewed in Dec 2023. There was 1 interview round.

Round 1 - One-on-one 

(3 Questions)

  • Q1. What are Large Language Models?
  • Ans. 

    Large Language Models are advanced AI models that can generate human-like text based on input data.

    • Large Language Models use deep learning techniques to understand and generate text.

    • Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).

    • They are trained on vast amounts of text data to improve their language generation capabilities.

  • Answered by AI
  • Q2. Do you know about RAGs?
  • Ans. 

    RAGs stands for Red, Amber, Green. It is a project management tool used to visually indicate the status of tasks or projects.

    • RAGs is commonly used in project management to quickly communicate the status of tasks or projects.

    • Red typically indicates tasks or projects that are behind schedule or at risk.

    • Amber signifies tasks or projects that are on track but may require attention.

    • Green represents tasks or projects that ar...

  • Answered by AI
  • Q3. Which is the best clustering algorithm?
  • Ans. 

    There is no one-size-fits-all answer as the best clustering algorithm depends on the specific dataset and goals.

    • The best clustering algorithm depends on the dataset characteristics such as size, dimensionality, and noise level.

    • K-means is popular for its simplicity and efficiency, but may not perform well on non-linear data.

    • DBSCAN is good for clusters of varying shapes and sizes, but may struggle with high-dimensional d...

  • 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 and was interviewed in Jun 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Some basic aptitude questions were asked , but had to be solved in 20 minutes

Round 2 - Coding Test 

Medium level 2 leet code questions were asked and i cleared both

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

I was interviewed in Dec 2023.

Round 1 - Aptitude Test 

English, number system, grammar

Round 2 - Coding Test 

Python , data science, machine learning

Round 3 - Assignment 

Python machine learning, natural language precossing

Round 4 - HR 

(4 Questions)

  • Q1. Python , Data Science, SQL
  • Q2. What is python basics, libraries
  • Ans. 

    Python basics include syntax, data types, and control structures. Libraries like NumPy, Pandas, and Matplotlib enhance data analysis and visualization.

    • Python basics cover syntax, variables, data types, and control structures.

    • NumPy is a library for numerical computing, providing powerful array operations.

    • Pandas is a library for data manipulation and analysis, offering data structures like DataFrames.

    • Matplotlib is a libr...

  • Answered by AI
  • Q3. Data science algorithms , and theory
  • Q4. Sql querys, cluases
Round 5 - Group Discussion 

Indian environment, village, college days

Round 6 - HR 

(1 Question)

  • Q1. Python, data science
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Dec 2023. There was 1 interview round.

Round 1 - HR 

(3 Questions)

  • Q1. How many working days
  • Q2. Company give another benefit
  • Q3. Work load is high or low
Round 1 - Technical 

(1 Question)

  • Q1. Basic python and machine learning questions
Round 2 - HR 

(1 Question)

  • Q1. Salary expectation and working location related questions and why you want to join wipro

Interview Preparation Tips

Interview preparation tips for other job seekers - Focus on basic python and machine learning

ONLEI Technologies Interview FAQs

How many rounds are there in ONLEI Technologies Data Science Intern interview?
ONLEI Technologies interview process usually has 1-2 rounds. The most common rounds in the ONLEI Technologies interview process are Aptitude Test and Coding Test.
What are the top questions asked in ONLEI Technologies Data Science Intern interview?

Some of the top questions asked at the ONLEI Technologies Data Science Intern interview -

  1. Hsjfbfthehfbf fauzia hii ...read more
  2. Ndjf Ncjfhf...read more

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ONLEI Technologies Data Science Intern Reviews and Ratings

based on 19 reviews

4.6/5

Rating in categories

4.4

Skill development

4.6

Work-life balance

4.4

Salary

4.5

Job security

4.6

Company culture

4.5

Promotions

4.5

Work satisfaction

Explore 19 Reviews and Ratings
Data Analyst Intern
4 salaries
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₹1 L/yr - ₹12 L/yr

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