Sugal & Damani Data Scientist Interview Questions and Answers

Q1. Tell me about Yourself.
Ans. 
I am a data scientist with a background in statistics and machine learning.
• Background in statistics and machine learning

• Experience with data analysis and visualization tools like Python, R, and Tableau

• Strong problem-solving skills

• Ability to communicate complex technical concepts to non-technical stakeholders
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Q2. Explain your Final Year Project
Ans. 
Developed a predictive model for customer churn in a telecom company using machine learning algorithms.
• Used Python for data preprocessing and model building

• Implemented algorithms like Random Forest and Logistic Regression

• Evaluated model performance using metrics like accuracy and AUC-ROC curve
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Data Science MCQ questions

Building a baseline ML model with EDA etc.

Q1. How do you analyse outliers?
Ans. 
Outliers can be analyzed using statistical methods like Z-score, IQR, or visualization techniques like box plots.
• Calculate Z-score and identify data points with Z-score greater than a certain threshold as outliers.

• Use Interquartile Range (IQR) to detect outliers by identifying data points outside 1.5 * IQR range.

• Visualize data using box plots to identify any data points that fall outside the whiskers.

• Consider domain kn...read more
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Q2. Tell me about a time when what you found did not match expectation with what you thought analysing the dataset.
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Q1. Why Unilever now?
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Q2. Where do you see yourself in 5 years?
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Q1. Tell me about yourself
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Q2. Questions from projects which was mentioned on resume
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Q1. Fitment based questions
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Q2. Explain a project
Ans. 
Developed a machine learning model to predict customer churn for a telecom company.
• Collected and cleaned customer data including usage patterns and demographics

• Used classification algorithms like Random Forest and Logistic Regression to build the model

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

Q1. Asked me about expected salary
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Q1. What is difference between lstm and rnn
Ans. 
LSTM is a type of RNN that addresses the vanishing gradient problem by using memory cells.
• RNN stands for Recurrent Neural Network, a type of neural network that processes sequential data.

• LSTM stands for Long Short-Term Memory, a type of RNN that includes memory cells to retain information over long sequences.

• LSTM is designed to overcome the vanishing gradient problem, which occurs when training RNNs on long sequences.

• L...read more
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Q1. What are different evaluation matrix ?
Ans. 
Evaluation matrices are used to assess the performance of models in data science.
• Confusion matrix: used to evaluate the performance of classification models.

• Precision, recall, and F1 score: measures for binary classification models.

• Mean squared error (MSE): evaluates the performance of regression models.

• R-squared: assesses the goodness of fit for regression models.

• Area under the ROC curve (AUC-ROC): evaluates the perfo...read more
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Q1. Tell us data science project where you developed a script for forecastings, KNN, Data science models with practical examples.
Ans. 
Developed a script for forecasting using KNN and data science models.
• Developed a script using Python to forecast sales for a retail company using KNN algorithm.

• Built a data science model to predict customer churn for a telecom company using logistic regression.

• Used time series analysis to forecast stock prices for a financial services company.

• Developed a script to predict the likelihood of a customer defaulting on a lo...read more
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Q2. 1. Why you are asking this role is for Data analyst or data scientist? 2. Don't go for the provided JD and do you think you are well aware of Data science concepts and models, algorithms etc.
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Q1. Explain about some of visualization tools
Ans. 
Visualization tools are software applications used to create graphical representations of data for easier understanding and analysis.
• Popular visualization tools include Tableau, Power BI, and Google Data Studio.

• These tools allow users to create interactive charts, graphs, and dashboards.

• They support various data sources and formats, making it easy to import and visualize data.

• Visualization tools help in identifying pat...read more
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Mettle test and mcq were given in interview