Data Science Associate Interview Questions and Answers

Factors to consider for increasing sales in Domino's Indonesia and methodology for creating a CLM for increasing ROI

• Analyze customer demographics and preferences

• Evaluate competition and market trends

• Assess pricing and promotional strategies

• Optimize delivery and supply chain operations

• Implement loyalty programs and personalized marketing

• Track and measure key performance indicators

• Create a customer lifecycle management plan based on insights

• Continuously iterate and improve the ...read more

Supervised learning problems involve predicting an output variable based on input data with labeled examples.

• Classification: Predicting a categorical label (e.g. spam/not spam)

• Regression: Predicting a continuous value (e.g. house prices)

• Ranking: Predicting the order of a set of items (e.g. search engine results)

Data science is a field that involves using statistical and computational methods to extract insights from data.

• Data science involves collecting, cleaning, and analyzing data

• It uses statistical and machine learning techniques to build models and make predictions

• Data visualization is an important aspect of data science

• It has applications in various fields such as finance, healthcare, and marketing

• Python and R are popular programming languages used in data science

Box-plot is a visual representation of the distribution of a dataset, showing the median, quartiles, and outliers.

• Box-plot displays the median (middle line), quartiles (box), and outliers (dots or lines).

• The length of the box represents the interquartile range (IQR).

• Whiskers extend to the smallest and largest non-outlier data points within 1.5 times the IQR from the quartiles.

• Outliers are plotted individually as dots or lines beyond the whiskers.

• Box-plots are useful for compa...read more

Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.

• Logistic regression is used when the dependent variable is binary (0/1, True/False, Yes/No, etc.).

• It estimates the probability that a given observation belongs to a particular category.

• The output of logistic regression is a probability score between 0 and 1.

• It uses the logistic function (sigmoid function) to model the relationship between the...read more

Standardisation and normalisation are techniques used to scale and transform data in order to improve model performance.

• Standardisation (Z-score normalisation) scales the data to have a mean of 0 and a standard deviation of 1.

• Normalisation (Min-Max scaling) scales the data to a specific range, typically between 0 and 1.

• Standardisation is less affected by outliers compared to normalisation.

• Standardisation is preferred when the data follows a normal distribution, while normalis...read more

Classification metrics are used to evaluate the performance of machine learning models in predicting categorical outcomes.

• Common classification metrics include accuracy, precision, recall, F1 score, and ROC-AUC.

• Accuracy measures the proportion of correctly classified instances out of total instances.

• Precision measures the proportion of true positive predictions out of all positive predictions.

• Recall measures the proportion of true positive predictions out of all actual positi...read more

Machine learning types include supervised learning, unsupervised learning, and reinforcement learning.

• Supervised learning involves training a model on labeled data to make predictions.

• Unsupervised learning involves finding patterns in unlabeled data.

• Reinforcement learning involves learning through trial and error based on rewards and punishments.