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Capgemini Senior Data Science Consultant Interview Questions and Answers
Capgemini Senior Data Science Consultant Interview Experiences
1 interview found
Mohan Singh
Selected
I applied via Approached by Company and was interviewed in Dec 2023. There were 3 interview rounds.
(6 Questions)
- Q1. Why CNN is preferred over feed forward neural networks ?
- Ans.
CNN is preferred over feed forward neural networks due to their ability to capture spatial and temporal dependencies in data.
CNNs are designed to effectively capture spatial relationships in data, making them ideal for tasks like image recognition.
CNNs use shared weights and local connectivity to efficiently learn patterns in data, reducing the number of parameters compared to feed forward neural networks.
CNNs are also...
- Q2. Problem based linear regression questions, basically about identifying the actual relationship between IV and DV variables.
- Q3. If dealing with non-linearity with same data as in above question, which algo to prefer ? Typically it was on polynomial regression and how we choose the degree there ?
- Q4. Explain overfitting and underfitting ? Techniques to avoid this
- Ans.
Overfitting occurs when a model learns noise in the training data rather than the underlying pattern, while underfitting occurs when a model is too simple to capture the underlying pattern.
Overfitting: Model performs well on training data but poorly on unseen data. Can be avoided by using techniques like cross-validation, regularization, and early stopping.
Underfitting: Model is too simple to capture the underlying pat...
- Q5. Explain cross validation and its process of working
- Ans.
Cross validation is a technique used to assess the performance of a predictive model by splitting the data into training and testing sets multiple times.
Divide the data into k subsets (folds)
Train the model on k-1 folds and test on the remaining fold
Repeat this process k times, each time using a different fold as the test set
Calculate the average performance metric across all k iterations to evaluate the model
- Q6. Python based few things
It was basically conceptual round with the vp. There were General questions about the studies, projects, data science journey etc.
And then an use case. I don't remember exactly but it was something like..
Different companies sales their different models of cars and providing incentives which are not coming through dealers obviously..infact from manufacturer itself.
Few more things on this and then questions like-
How would you convert this into an analytics problem?
What kind of data would be required to perform such analysis?
If you are dealing with regression problem but time is involved there, how you will solve that now ?
Some things on trend, seasonality in time series analysis, about arima.
Basically statistical kind of round but based on business scenarios.
Hope that helps😉
(1 Question)
- Q1. Simple things on Salary discussions, expectations etc.
Interview Preparation Tips
Skills evaluated in this interview
Interview questions from similar companies
Aman Jaiswal
I applied via Campus Placement
(2 Questions)
- Q1. Design a dwmand planning system
- Ans.
Design a demand planning system for efficient forecasting and inventory management.
Utilize historical sales data to identify trends and seasonality
Incorporate external factors like market trends, promotions, and competitor activities
Implement machine learning algorithms for accurate demand forecasting
Integrate with inventory management systems for optimized stock levels
Regularly review and adjust the system based on pe
- Q2. Pick one point from resume and explain
- Ans.
Implemented machine learning model to predict customer churn for a telecom company
Developed and trained a machine learning model using Python and scikit-learn
Utilized historical customer data to identify patterns and factors leading to churn
Evaluated model performance using metrics such as accuracy, precision, and recall
Provided actionable insights to the telecom company based on the model's predictions
Skills evaluated in this interview
I applied via Campus Placement
(1 Question)
- Q1. ML and deep learning questions
(2 Questions)
- Q1. Projects discussion
- Q2. Chatgpt architecture
I applied via Job Fair
(51+52+53+......+100) =
(4 Questions)
- Q1. M.s excel , red hat ,
- Q2. Introdution M.s word
- Q3. Linux , git , mavel , nexus.
- Q4. Sonar cube , aws , super putty.
Interview Preparation Tips
Selected
I applied via campus placement at Chennai Mathematical Institute, Chennai and was interviewed in Dec 2023. There was 1 interview round.
(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.
- 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...
- 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...
Skills evaluated in this interview
Selected
I applied via Job Portal and was interviewed in Oct 2023. There were 4 interview rounds.
Coding test is important
Most important in coding test
Group discussion is share the projects many people one idea
(1 Question)
- Q1. Last round in HR round in salary details joining in company
Data Science Engineer Interview Questions & Answers
Cognizant
Aila Chanakya Darahas
posted on 16 Feb 2024
Good execellnt and well done
(2 Questions)
- Q1. Tell me your self
- Q2. Tell me why cogniznt
Selected
(3 Questions)
- Q1. Always prepare projects u have worked on in STAR format.
- Q2. Tell me about yourself .
- Q3. Explain any 4 projects in STAR format
- Ans.
Developed a recommendation system for an e-commerce website
Used collaborative filtering to recommend products to users
Implemented the system using Python and Apache Spark
Evaluated the system's performance using precision and recall metrics
Improved the system's performance by incorporating user feedback
Interview Preparation Tips
And explain projects in STAR format.
I applied via Approached by Company and was interviewed in May 2022. There were 4 interview rounds.
(2 Questions)
- Q1. Difference between evar and prop
- Ans.
eVar is a conversion variable that captures values at the time of conversion, while prop is a traffic variable that captures values at the time of page view.
eVar captures values at the time of conversion, while prop captures values at the time of page view.
eVar is used to track conversion events, while prop is used to track traffic events.
eVar is persistent across visits, while prop is not.
Example: eVar can capture the...
- Q2. What is clustering and classification
- Ans.
Clustering is grouping similar data points together while classification is assigning labels to data points based on their features.
Clustering is unsupervised learning while classification is supervised learning.
Clustering algorithms include K-means, hierarchical clustering, and DBSCAN.
Classification algorithms include decision trees, logistic regression, and support vector machines.
Clustering is used for customer segm...
(2 Questions)
- Q1. Case study questions related to Data Science
- Q2. Why i want to join
(2 Questions)
- Q1. What is reason i am leaving previous company
- Q2. Team handling experience
Interview Preparation Tips
Skills evaluated in this interview
I applied via Approached by Company and was interviewed in Jun 2022. There were 3 interview rounds.
(1 Question)
- Q1. Details of interview person and family details and address and personal information and other study performance Ramya mother father brother Borigama inchoda
(2 Questions)
- Q1. How to do work yours
- Q2. Hiw to do spend time
Interview Preparation Tips
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Capgemini Senior Data Science Consultant Interview Process
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