Dunnhumby Senior Applied Data Scientist Interview Questions and Answers

Q1. What's the CI/CD workflow that's followed in your team?
Ans. 
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 cont...read more
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Q2. Has there been any security incident and how have you handled those ?
Ans. 
Yes, there have been security incidents and I have handled them effectively.
• Implemented security protocols to prevent future incidents

• Conducted thorough investigation to identify the root cause

• Collaborated with IT team to strengthen security measures

• Communicated with stakeholders to ensure transparency and trust

• Provided training to employees on cybersecurity best practices
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Q3. Difference between authorization and authentication ?
Ans. 
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 denyin...read more
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Q4. LLD for an authentication and authorization system
Ans. 
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
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Q1. Design a document managed storage like google drive as an E2E solution.
Ans. 
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 app
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Q1. Explain the RAG pipeline?
Ans. 
RAG pipeline is a data processing pipeline used in data science to categorize data into Red, Amber, and Green based on certain criteria.
• RAG stands for Red, Amber, Green which are used to categorize data based on certain criteria

• Red category typically represents data that needs immediate attention or action

• Amber category represents data that requires monitoring or further investigation

• Green category represents data that...read more
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Q2. Explain Confusion metrics
Ans. 
Confusion metrics are used to evaluate the performance of a classification model by comparing predicted values with actual values.
• Confusion matrix is a table that describes the performance of a classification model.

• It consists of four different metrics: True Positive, True Negative, False Positive, and False Negative.

• These metrics are used to calculate other evaluation metrics like accuracy, precision, recall, and F1 s...read more
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I was asked to write SQL queries for 3rd highest salary of the employee, some name filtering, group by tasks.
Python code to find the index of the maximum number without using numpy.

Q1. Explain the Project undertaken during the research and follow-up questions
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Q1. Write pandas query to separate the names as first and last name from the full name. Drop the duplicate columns and also the missing values. Write output for the Python code. Write SQL query to retrieve t...read more
Ans. 
Answering questions related to data science concepts and techniques.
• Recall is the ratio of correctly predicted positive observations to the total actual positives. Precision is the ratio of correctly predicted positive observations to the total predicted positives.

• To reduce variance in an ensemble model, techniques like bagging, boosting, and stacking can be used. Bagging involves training multiple models on different ...read more
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Q1. Questions related to python basics.
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Q2. Basic calculus to test math skills.
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Q3. Machine learning metrics.
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Q1. Policies, behavioral round.
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Q2. Work culture and the selection process.
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Q3. Discussion about previous employers and educational background.
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