30+ Decision Scientist Interview Questions and Answers

Explanation of significance of mean and standard deviation in normal distribution.

• Mean represents the central tendency of the data while standard deviation measures the spread of the data.

• In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, 95% within two standard deviations, and 99.7% within three standard deviations.

• These percentages can be used to calculate the probability of a data point falling within a certain range of...read more

There are approximately 500 sweet shops in my city.

• The number of sweet shops may vary depending on the size of the city.

• Factors such as population density and cultural preferences may also affect the number of sweet shops.

• A rough estimate can be made by dividing the population by the number of sweet shops per capita in similar cities.

• Alternatively, a survey or data analysis of existing sweet shops can provide a more accurate estimate.

I stay up to date with new analytical tools and techniques by attending workshops, online courses, reading research papers, and participating in industry conferences.

• Attend workshops and training sessions on new tools and techniques

• Take online courses and certifications to learn about the latest advancements

• Read research papers and articles to stay informed about cutting-edge methods

• Participate in industry conferences and networking events to exchange knowledge and ideas

Z test is used when sample size is large and population standard deviation is known. T test is used when sample size is small or population standard deviation is unknown.

• Z test is used for hypothesis testing when sample size is large (n > 30) and population standard deviation is known.

• T test is used when sample size is small (n < 30) or population standard deviation is unknown.

• Z test is used for comparing means of two populations when the population standard deviation is know...read more

Chi square test is a statistical test used to determine if there is a significant association between two categorical variables.

• Chi square test is used to compare observed frequencies with expected frequencies in a contingency table.

• It is commonly used in research to analyze data and determine if there is a relationship between two variables.

• For example, it can be used to test if there is a significant difference in the distribution of a disease between two groups.

• Another exa...read more

Utilized K-means clustering to group customers based on purchasing behavior. Evaluated clusters using silhouette score and inertia.

• Used K-means clustering algorithm to group customers into segments

• Evaluated the quality of clusters using silhouette score and inertia

• Silhouette score measures how similar an object is to its own cluster compared to other clusters

• Inertia measures how tightly the clusters are packed together

• Example: Clustered customers based on demographics and pur...read more

Use SQL window function to calculate monthwise cumulative sum.

• Use the SUM() function with OVER() clause to calculate cumulative sum.

• Partition the data by month to get monthwise cumulative sum.

• Order the data by date to ensure correct cumulative sum calculation.

I am passionate about uncovering insights and patterns in data to drive informed decision-making.

• I enjoy working with numbers and finding trends in data sets.

• Analyzing data allows me to make strategic decisions based on evidence rather than intuition.

• I find satisfaction in solving complex problems using statistical methods and algorithms.

Developed predictive model to forecast customer churn using machine learning algorithms

• Collected and cleaned customer data from various sources

• Performed feature engineering to create relevant predictors

• Built and trained machine learning models such as logistic regression and random forest

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

• Implemented the model in a production environment for real-time predictions

Stats focuses on summarizing and interpreting data, while data analysis involves exploring and drawing insights from data.

• Statistics involves collecting, organizing, analyzing, and interpreting data to make informed decisions.

• Data analysis involves cleaning, transforming, and visualizing data to discover patterns, trends, and insights.

• Statistics uses mathematical formulas and techniques to summarize data, such as mean, median, and standard deviation.

• Data analysis uses tools l...read more

Binomial distribution is a probability distribution that describes the number of successes in a fixed number of independent trials.

• Describes the number of successes in a fixed number of independent trials

• Each trial has only two possible outcomes (success or failure)

• The trials are independent and the probability of success is constant

• Examples: Coin toss (success = heads), Pass/fail exams, Yes/no surveys

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

• Central Limit Theorem is a fundamental concept in statistics.

• It states that the sampling distribution of the sample mean will be approximately normally distributed regardless of the shape of the population distribution.

• As the sample size increases, the sampling distribution of the sample mean becomes more normally distributed.

• It is used ...read more

K-means clustering is a popular unsupervised machine learning algorithm used for clustering data points into groups based on similarity.

• Divides data points into K clusters based on similarity

• Minimizes the sum of squared distances within each cluster

• Requires specifying the number of clusters (K) beforehand

• Iteratively assigns data points to the nearest cluster centroid

• Commonly used in customer segmentation, image compression, and anomaly detection

SQL queries are executed in a specific order to ensure accurate results.

• SQL queries are executed in the following order: SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY.

• The SELECT clause is always executed first to retrieve the specified columns.

• The FROM clause is then executed to specify the tables from which to retrieve data.

• The WHERE clause filters the rows based on specified conditions.

• The GROUP BY clause groups the rows based on specified columns.

• The HAVING clause filter...read more

Precision-Recall AUC is a metric used to evaluate the performance of classification models, particularly in imbalanced datasets.

• Precision-Recall AUC focuses on the trade-off between precision and recall for different threshold values.

• It is particularly useful when dealing with imbalanced datasets where the positive class is rare.

• A higher Precision-Recall AUC indicates better model performance in terms of precision and recall.

• It is often used in conjunction with the ROC AUC me...read more

Data is information collected and analyzed for decision-making. Mu Sigma is a leading analytics company.

• Data is raw facts and figures that can be processed to gain insights.

• Mu Sigma is a data analytics company that helps businesses make data-driven decisions.

• Data can come in various forms such as structured, unstructured, and semi-structured.

• Mu Sigma uses advanced analytics techniques like machine learning and AI to extract valuable insights from data.

• Data is essential for bu...read more

Recommendation system uses data analysis and machine learning algorithms to suggest items to users based on their preferences.

• Collect user data and item data

• Analyze data to find patterns and similarities

• Use machine learning algorithms to make predictions and suggest items to users

• Continuously update and improve the system based on user feedback

• Examples: Netflix suggesting movies based on viewing history, Amazon suggesting products based on purchase history

Cross validation is a technique used to evaluate the performance of a machine learning model by testing it on multiple subsets of the data.

• It involves dividing the data into multiple subsets or folds.

• The model is trained on a subset and tested on the remaining subset.

• This process is repeated for all subsets and the results are averaged to get a final performance metric.

• It helps to prevent overfitting and provides a more accurate estimate of the model's performance.

• Examples in...read more

Vodafone Idea is a telecom company in India facing financial challenges due to intense competition and regulatory issues.

• Vodafone Idea is struggling to compete with other telecom companies in India such as Reliance Jio and Bharti Airtel.

• The company has a large debt burden and has been unable to raise funds due to regulatory issues.

• Vodafone Idea has been losing subscribers and market share due to poor network quality and customer service.

• The Indian government has recently anno...read more

A confusion matrix is a table used to evaluate the performance of a classification model.

• It shows the number of true positives, true negatives, false positives, and false negatives.

• It helps in calculating various evaluation metrics like accuracy, precision, recall, and F1 score.

• It is useful in comparing the performance of different models.

• Example: A confusion matrix for a binary classification problem can be represented as follows: | | Predicted Positive | Predicted Negative ...read more

ML solves complex problems by analyzing data and making predictions or decisions based on patterns and trends.

• ML can solve problems related to prediction, classification, clustering, anomaly detection, and recommendation.

• Examples include predicting customer churn, classifying spam emails, clustering similar customer segments, detecting fraudulent transactions, and recommending products based on user behavior.

• ML can automate tasks that are too complex or time-consuming for hum...read more

Python code using recursion

• Recursion is a technique in which a function calls itself to solve a problem

• Base case is important to prevent infinite recursion

• Example: Factorial calculation using recursion - def factorial(n): return 1 if n == 0 else n * factorial(n-1)

Inheritance is the mechanism in object-oriented programming where a new class inherits attributes and methods from an existing class.

• Inheritance allows for code reusability and promotes the concept of hierarchical classification.

• The class that is being inherited from is called the parent class or superclass, while the class that inherits is called the child class or subclass.

• Subclasses can add new attributes or methods, or override existing ones from the superclass.

• Example: A...read more

Different types of SQL joins include inner join, left join, right join, and full outer join.

• Inner join: Returns rows when there is a match in both tables

• Left join: Returns all rows from the left table and the matched rows from the right table

• Right join: Returns all rows from the right table and the matched rows from the left table

• Full outer join: Returns rows when there is a match in either table

Types of joins in SQL include inner join, left join, right join, and full outer join.

• Inner join: Returns rows when there is a match in both tables

• Left join: Returns all rows from the left table and the matched rows from the right table

• Right join: Returns all rows from the right table and the matched rows from the left table

• Full outer join: Returns rows when there is a match in either table

Reverse a given string

• Use built-in functions like reverse() or loop through the string

• Create a new string and add characters in reverse order

• Handle edge cases like empty string or single character

Tree models are predictive models that use a tree-like graph of decisions and their possible consequences.

• Tree models split the data into subsets based on the most significant attributes.

• They are used for classification and regression tasks.

• Examples include decision trees, random forests, and gradient boosting trees.

I use a variety of tools depending on the task at hand, including Python, R, SQL, Excel, and Tableau.

• Python for data cleaning and analysis

• R for statistical modeling and visualization

• SQL for querying and manipulating databases

• Excel for basic data analysis and visualization

• Tableau for creating interactive dashboards and visualizations