Decision Scientist
40+ Decision Scientist Interview Questions and Answers

Asked in Mu Sigma

Q. Stats- Significance of Mean and Standard Deviation. Normal distribution, percentage distribution for every SD in Normal distribution
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

Asked in Mu Sigma

Q. Estimate the number of sweet shops in your city.
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.
Decision Scientist Interview Questions and Answers for Freshers

Asked in C2fo

Q. How do you stay up to date with new analytical tools and techniques?
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

Asked in Mu Sigma

Q. What's the CI/CD workflow that's followed in your team?
Our team follows a CI/CD workflow that includes automated testing, code reviews, and continuous integration.
Automated testing is run on every code change to catch bugs early.
Code reviews are conducted before merging changes to ensure code quality.
Continuous integration is used to automatically build and test code changes in a shared repository.
Deployment pipelines are set up to automate the release process.
Version control is used to track changes and manage codebase effective...read more

Asked in C2fo

Q. When is a z test used and when is t test used.
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

Asked in Mu Sigma

Q. Case Study: How can you increase the growth of a leading mobile manufacturer?
Enhancing growth for a leading mobile manufacturer involves innovation, market expansion, and customer engagement strategies.
Invest in R&D to develop cutting-edge features, like foldable screens or advanced AI capabilities.
Expand into emerging markets, such as Africa and Southeast Asia, where smartphone penetration is still growing.
Enhance customer engagement through loyalty programs and personalized marketing campaigns.
Collaborate with app developers to create exclusive apps...read more
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Asked in Mu Sigma

Q. What is the difference between data and a data source?
Data is the information collected and stored, while data source is the origin or location from which the data is obtained.
Data is the raw facts and figures that are collected and stored for analysis.
Data source is the location or system from which the data is collected, such as a database, sensor, or survey.
Examples of data sources include customer surveys, website analytics, and social media platforms.

Asked in C2fo

Q. What is the Chi-Square test, and when is it used?
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
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Asked in Mu Sigma

Q. Design a document managed storage system like Google Drive as an E2E solution.
Design a document managed storage like Google Drive as an E2E solution.
Implement user authentication and authorization for secure access.
Create a user-friendly interface for uploading, organizing, and sharing documents.
Include features like version control, file syncing, and search functionality.
Utilize cloud storage for scalability and accessibility.
Implement encryption for data security.
Integrate with third-party apps for enhanced functionality.

Asked in C2fo

Q. Write a SQL query to find the month-wise cumulative sum of a given metric.
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.

Asked in Amazon

Q. What is the most challenging problem you have solved or tried to solve?
Developing a predictive model for customer churn in a telecom company
Gathering and cleaning large amounts of customer data
Identifying key predictors of churn through statistical analysis
Building and testing various machine learning models
Iteratively refining the model to improve accuracy
Presenting findings and recommendations to stakeholders

Asked in Infosys

Q. What is the difference between authorization and authentication?
Authentication verifies the identity of a user, while authorization determines what actions a user is allowed to perform.
Authentication confirms the identity of a user through credentials like passwords or biometrics.
Authorization determines the level of access or permissions a user has once their identity is confirmed.
Authentication is the process of logging in, while authorization is the process of granting or denying access to resources.
Example: Logging into a bank account...read more

Asked in C2fo

Q. Clustering project explanation and clustering metrics used.
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

Asked in EXL Service

Q. What is overfitting?
Overfitting occurs when a machine learning model learns noise instead of the underlying pattern, leading to poor generalization.
Overfitting happens when a model is too complex, capturing noise in the training data.
Example: A decision tree that perfectly classifies training data but fails on new data.
Signs of overfitting include high accuracy on training data but low accuracy on validation/test data.
Techniques to prevent overfitting include cross-validation, pruning, and regul...read more

Asked in Mu Sigma

Q. Why do you want to work with analytical data?
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.

Asked in Mu Sigma

Q. Give 14 points what you think about Mu Sigma
Mu Sigma is a leading data analytics and decision sciences firm that helps organizations make data-driven decisions.
Founded in 2004, Mu Sigma has grown to become a prominent player in the analytics space.
They focus on providing data analytics solutions to Fortune 500 companies across various industries.
Mu Sigma emphasizes a culture of continuous learning and innovation among its employees.
The company uses a unique blend of technology and human expertise to solve complex busin...read more

Asked in C2fo

Q. Explain a past project involving predictive modeling.
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

Asked in PhonePe

Q. Estimate the number of flights at Bengaluru airport.
The number of flights at Bengaluru airport can vary depending on the day and time, but on average, there are around 400-500 flights per day.
Consider the average number of flights per day at Bengaluru airport
Take into account the peak hours and off-peak hours for flight operations
Factor in the types of flights - domestic, international, cargo, etc.
Look at historical data or industry reports for more accurate estimates

Asked in Mu Sigma

Q. What is the difference between Statistics and Data Analysis?
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

Asked in Mu Sigma

Q. LLD for an authentication and authorization system
LLD for an authentication and authorization system
Separate modules for authentication and authorization
Use of secure hashing algorithms for storing passwords
Role-based access control implementation
Audit logging for tracking user actions
Integration with external identity providers

Asked in Mu Sigma

Q. Explain your contributions to the house price model.
I developed a predictive model to estimate house prices based on various factors.
Collected and cleaned data on house features, location, and sale prices
Performed exploratory data analysis to identify key variables impacting house prices
Built and trained machine learning models such as linear regression or random forest
Evaluated model performance using metrics like RMSE or R-squared
Used the model to make predictions on new data and assess accuracy

Asked in C2fo

Q. What is binomial distribution?
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

Asked in QBS Learning

Q. What is K-means clustering?
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

Asked in Six Red Marbles

Q. What is the central limit theorem?
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

Asked in C2fo

Q. What are precision, recall, and AUC?
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

Asked in Mu Sigma

Q. What is the order of execution of an SQL query?
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

Asked in Mu Sigma

Q. What is Data and Why Mu Sigma
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

Asked in Dream11

Q. Explain how a recommendation system works.
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

Asked in Bajaj Finserv

Q. What is cross-validation?
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

Asked in Mu Sigma

Q. case steady of vodafone idea
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
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