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Yubi Data Scientist Interview Questions and Answers
Yubi Data Scientist Interview Experiences
3 interviews found
Anonymous
Sql and pandas problems along mcqs on ML
(2 Questions)
- Q1. Linear Regression
- Q2. Basic Neural Network Implementation
(2 Questions)
- Q1. Question about working of BERT
- Q2. Word2vec explanation
- Ans.
Word2vec is a technique used to create word embeddings by training a neural network on a large corpus of text.
Word2vec is a shallow neural network model that learns to represent words as vectors in a continuous vector space.
It captures semantic relationships between words by placing similar words close together in the vector space.
There are two main architectures for Word2vec: Continuous Bag of Words (CBOW) and Skip-gr...
Skills evaluated in this interview
Selected
I applied via Referral and was interviewed in Jul 2024. There were 2 interview rounds.
(1 Question)
- Q1. Question regarding my resume .It is technical interview
Case study-this is about loan default prediction assignment
Selected
I applied via Referral and was interviewed before Feb 2023. There was 1 interview round.
(2 Questions)
- Q1. What is clustering
- Ans.
Clustering is a technique used in data analysis to group similar data points together based on their characteristics.
Clustering is an unsupervised learning method.
It helps in identifying patterns and relationships in data.
Common clustering algorithms include K-means, hierarchical clustering, and DBSCAN.
Example: Grouping customers based on their purchasing behavior.
Example: Identifying different species of flowers based
- Q2. How to avoid overfitting
- Ans.
To avoid overfitting, use techniques like cross-validation, regularization, and increasing training data.
Use cross-validation to evaluate model performance on unseen data
Apply regularization techniques like L1 or L2 regularization to penalize complex models
Increase the size of the training dataset to provide more diverse examples
Use feature selection or dimensionality reduction methods to reduce the complexity of the m...
Interview Preparation Tips
Skills evaluated in this interview
Data Scientist Jobs at Yubi
Interview questions from similar companies
Interview Preparation Tips
Experience: The technical interview included a VP round which was more of a resume round. I concentrated my interview (VP round) on Machine learning which my field is. This was kind of a trick because many people screwed up this round. Hence, VP offered to me to work in VISA HQ.
Round: Technical Interview
Experience: This technical round included questions from almost all topics of CS (SQL query, coding, Networks, Security, Hadoop and Map-Reduce).
General Tips: Do’s :
1) Start right from August
2) Prepare basics of subjects
3) Try to code using pen and paper
4) Code as many problems as you can from all domains with only 1 language (C/C++/Java)
5) Keep a friend with you at all times during interviews. If you are selected for more than 1
companies in 1 slot, ask your friend to manage your interview schedules given he knows your
priorities. I was not in a position to attend more than 2 interviews in the same slot.
Don’ts :
1) Don’t lose hope if you are not shortlisted for your dream company or any company of your choice because being an IITian you have large number of better choices and which would fit in your profile better.
2) Don’t argue with the interviewers and never pretend that you are over smart in a given domain.
3) Do not take HR rounds lightly even if you are sitting for CS companies.
Final Tips :
Start your preparation early. Placement is 90% preparation and 10% luck.
College Name: IIT Kanpur
Pranjal Singh
Interview Preparation Tips
Duration: 120 minutes
Total Questions: 42
Round: Test
Experience: There was a test for VISA which had following sections:
Assessment Composition:
1. Coding Skills: 2 Questions - Very simple problems - 30 marks total
2. Programming: 10 Questions - Simple Java Questions --Access modifiers, inline function, Red black tree, heap
3. Machine Learning Hadoop MCQ: 6 Questions You can't answer a single question if ML/BigData is remote-land for you.
4. Networking MCQ: 6 Questions - Again basics. Data layer questions. IP class basic question, fields in ethernet header.
5. Operating System: 6 Questions - Memory management mostly
6. Infrastructure: 6 Questions - Real life scenarios - server client questions.
7. Application Security: 6 Questions
Duration: 120 minutes
Total Questions: 42
Round: Interview
Experience: Questions from all CS subjects including coding
Tips: They shortlisted 29 students for the final interviews on Day 1 Slot 1.
There were 2 rounds of technical interview and 1 interview.
General Tips: Do’s
1) Start right from August
2) Prepare basics of subjects
3) Try to code using pen and paper
4) Code as many problems as you can from all domains with only 1 language (C/C++/Java)
5) Keep a friend with you at all times during interviews. If you are selected for more than 1 companies in 1 slot, ask your friend to manage your interview schedules given he knows your priorities. I was not in a position to attend more than 2 interviews in the same slot.
Don’ts
1) Don’t lose hope if you are not shortlisted for your dream company or any company of your choice because being an IITian you have large number of better choices and which would fit in your profile better.
2) Don’t argue with the interviewers and never pretend that your are over smart in a given domain.
3) Do not take HR rounds lightly even if you are sitting for CS companies.
Skills: C++
College Name: IIT Kanpur
Motivation: Role of my interest
First Question is basic coding question (Term frequecy of words).
Then a case study.
Basic ML questions.
Selected
I applied via Campus Placement and was interviewed before Jul 2023. There were 4 interview rounds.
Basic questions like stats, probability etc
Scenario based question
(1 Question)
- Q1. Questions on fundamentals
(1 Question)
- Q1. General questions
I applied via LinkedIn and was interviewed in Jun 2022. There were 2 interview rounds.
(3 Questions)
- Q1. What is rnn and lstm
- Ans.
RNN stands for Recurrent Neural Network and LSTM stands for Long Short-Term Memory. They are types of neural networks used for sequential data processing.
RNN is a type of neural network that can process sequential data by maintaining a memory of past inputs.
LSTM is a type of RNN that can handle the vanishing gradient problem and can remember long-term dependencies.
LSTM has gates that control the flow of information int...
- Q2. What is precision and recall
- Ans.
Precision and recall are two important metrics used to evaluate the performance of a classification model.
Precision measures the proportion of true positives among all the predicted positives.
Recall measures the proportion of true positives among all the actual positives.
Precision and recall are inversely related and a trade-off exists between them.
A high precision means that the model is good at predicting positive ca...
- Q3. What is regularisation
- Ans.
Regularisation is a technique used in machine learning to prevent overfitting by adding a penalty term to the loss function.
Regularisation helps to control the complexity of a model and reduce the impact of irrelevant features.
It adds a penalty term to the loss function, which encourages the model to have smaller weights.
There are different types of regularisation techniques such as L1 (Lasso) and L2 (Ridge) regularisa...
Interview Preparation Tips
- Deep Learning
- Machine Learning
- SQL
- Python
Skills evaluated in this interview
(2 Questions)
- Q1. DBSCAN Clustering
- Q2. How does current work helps solving use cases for PayU
- Ans.
My current work involves analyzing transaction data to identify patterns and trends, which can help PayU optimize their payment processing services.
Analyzing transaction data to identify fraudulent activities and improve security measures for PayU
Developing predictive models to forecast transaction volumes and optimize payment processing times
Utilizing machine learning algorithms to personalize user experiences and inc...
(2 Questions)
- Q1. When is your Availability
- Q2. Expectation from us
- Ans.
I expect a supportive work environment, opportunities for growth, and clear communication.
Clear communication on project goals and expectations
Opportunities for professional development and growth
Supportive team environment
Regular feedback and performance evaluations
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Yubi Data Scientist Interview Process
based on 3 interviews
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