PlaySimple Games Business Analyst Interview Questions and Answers for Freshers

My current project involves analyzing customer behavior on our e-commerce platform.

• Collecting and cleaning data from various sources

• Creating visualizations to identify patterns and trends

• Using statistical models to make predictions and recommendations

• Collaborating with cross-functional teams to implement changes

• Tracking and measuring the impact of changes on customer behavior

Developed a machine learning model to predict customer churn for a telecom company.

• Used logistic regression and decision tree algorithms for classification.

• Performed feature engineering to extract relevant features from customer data.

• Achieved an accuracy of 85% on the test set.

• Provided actionable insights to the company to reduce customer churn.

Different performance metrics are used to measure the effectiveness of a model or system.

• Accuracy

• Precision

• Recall

• F1 Score

• ROC Curve

• AUC

• Mean Squared Error

• Root Mean Squared Error

• R-squared

Bagging and boosting are ensemble learning techniques. XgBoost is a gradient boosting algorithm.

• Bagging involves training multiple models on different subsets of the data and combining their predictions.

• Boosting involves training models sequentially, with each model trying to correct the errors of the previous model.

• XgBoost is an optimized implementation of gradient boosting that uses a combination of tree-based models...read more