Accenture Data Scientist Interview Questions and Answers

Faced a performance issue in a React Native app due to heavy data processing, resolved by optimizing state management and using native modules.

• Identified performance bottlenecks using React Native's built-in performance monitor.

• Refactored state management by implementing Redux to manage complex state more efficiently.

• Utilized native modules for heavy computations, offloading tasks from the JavaScript thread.

• Conduc...read more

The Central Limit Theorem states that the distribution of sample means approaches a normal distribution as sample size increases.

• Definition: The Central Limit Theorem (CLT) states that the means of sufficiently large samples from a population will be normally distributed, regardless of the population's distribution.

• Sample Size: Typically, a sample size of 30 or more is considered sufficient for the CLT to hold tru...read more

Linear regression relies on several key assumptions to ensure valid results and interpretations of the model.

• Linearity: The relationship between the independent and dependent variables should be linear. For example, predicting house prices based on square footage.

• Independence: Observations should be independent of each other. For instance, the price of one house should not influence another's price.

• Homoscedasticit...read more

Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.

• Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

• Boosting involves training multiple models sequentially, where each subsequent mo...read more

I am proficient in Python, R, and SQL for data modeling and analysis.

• Python

• R

• SQL

Strategically locate the store in high foot traffic areas and tailor marketing to local demographics in Mumbai.

• Analyze foot traffic data to identify high-traffic areas like malls or busy markets.

• Consider demographics: target affluent neighborhoods for premium products.

• Utilize local festivals and events for marketing campaigns, e.g., Diwali promotions.

• Leverage social media to engage with local communities and promo...read more

Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern.

• Overfitting happens when a model is too complex and captures noise in the training data.

• It leads to poor generalization to new, unseen data.

• Techniques to prevent overfitting include cross-validation, regularization, and early stopping.

• Example: A decision tree with too many branches that perfectly fits the train...read more

To generate embeddings on a data set, preprocess the data, choose a suitable embedding method, train the model, and extract the embeddings.

• Preprocess the data by cleaning, tokenizing, and normalizing text data.

• Choose a suitable embedding method such as Word2Vec, GloVe, or FastText.

• Train the embedding model on the preprocessed data to learn the embeddings.

• Extract the embeddings from the trained model to represent t...read more