Societe Generale Global Solution Centre Data Scientist Interview Questions and Answers

NER training using deep learning

Q1. Describe the approach taken for assignment
Ans. 
I approach assignments by breaking them down into smaller tasks, setting deadlines, and regularly checking progress.
• Break down the assignment into smaller tasks to make it more manageable

• Set deadlines for each task to stay on track

• Regularly check progress to ensure everything is on schedule

• Seek feedback from colleagues or supervisors to improve the quality of work
Answered by AI
Add your answer
Q2. Scenario based questions
Add your answer

Q1. Tell me about yourself?
Ans. 
I am a data scientist with a background in statistics and machine learning, passionate about solving complex problems using data-driven approaches.
• Background in statistics and machine learning

• Experience in solving complex problems using data-driven approaches

• Passionate about leveraging data to drive insights and decision-making
Answered by AI
Add your answer
Q2. Describe in detail about one of my main project.
Ans. 
Developed a predictive model for 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.

• Implemented the model into the company's CRM system for real-time predictions.
Answered by AI
Add your answer
Q3. Few questions related to my projects.
Add your answer

Q1. Questions on Basics python(Since i am fresher)
Add your answer

They gave a span of 3 days to build an AI-powered webapp

Q1. How would you go about learning a new skill
Add your answer
Q2. Experience in cloud technologies
Ans. 
I have experience working with cloud technologies such as AWS, Azure, and Google Cloud Platform.
• Experience in setting up and managing virtual machines, storage, and networking in cloud environments

• Knowledge of cloud services like EC2, S3, RDS, and Lambda

• Experience with cloud-based data processing and analytics tools like AWS Glue and Google BigQuery
Answered by AI
Add your answer

Q1. Tell me about yourself
Add your answer
Q2. Project details and challenges faced in the project
Ans. 
Developed a predictive model for customer churn in a telecom company
• Collected and cleaned customer data from various sources

• Performed exploratory data analysis to identify key factors influencing churn

• Built and fine-tuned machine learning models to predict customer churn

• Challenges included imbalanced data, feature engineering, and model interpretability
Answered by AI
Add your answer

Easy test covering mathematics.

Given two medium to easy level questions.

Q1. As usual HR questions
Add your answer

Q1. Tell me about your self?
Add your answer
Q2. What is maths and stats
Ans. 
Maths and stats refer to the study of mathematical concepts and statistical methods for analyzing data.
• Maths involves the study of numbers, quantities, shapes, and patterns.

• Stats involves collecting, analyzing, interpreting, and presenting data.

• Maths is used to solve equations, calculate probabilities, and model real-world phenomena.

• Stats is used to make informed decisions, draw conclusions, and test hypotheses.

• Both ma...read more
Answered by AI
Add your answer

Confusion matrix what are your job rolls explain me Gradient boosting algorithm?

A="bala",b="Babu";
Print=A+b
O/p:
balababu

Python is a computer programming language use to build up software and websites designed by Rossum appear in 20 Feb 1991
1.Numpy is a python libraries working with arrays.
2.pandas is used to read the data sets.
3.matplotlib libraries for visualisation.
4.mission learning is divided into two parts.
*Supervised learning
*Unsupervised learning
5.deep learning is used to create artificial neurons.
6.advance excel is used for graphs and calculate the whole members at same time lot of useful things that have.
7mysql is mainly used for store the data.

Python, numpy, pandas, mission learning, deep learning, basic statistics, advance excel, MySQL

Python, numpy, pandas, mission learning, deep learning, basic statistics, advance excel, MySQL

Q1. Why we use mission learning Mission learning used for analysis the data's and we can able to predict and we add some additional algorithm it's mainly used for prediction and AI.
Ans. 
Mission learning is used for data analysis and prediction with additional algorithms for AI.
• Mission learning is a subset of machine learning that focuses on predicting outcomes based on data analysis.

• It involves using algorithms to learn patterns and make predictions based on new data.

• Examples include image recognition, natural language processing, and recommendation systems.
Answered by AI
Add your answer
Q2. Deep learning uses: Deep learning Mainly used for creating artificial neurons in the neural network. Deep learning is very aid about the mission how to work and artificial intelligence helps also
Add your answer
Q3. Statistics: Statistics is used for mathamatics operation and it helps to prediction. Example: We started to calculate how many persons live in between 20to25 age. That time statistics is very help to reduc...read more
Add your answer

I don't know idea about group discussion