Dunnhumby Data Science Engineer Interview Questions, Process, and Tips

Q1. Explain any ML model.
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Q2. Create Dataframe from two lists.
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1 hour aptitude test

Q1. What is one hot encoding
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Q1. What is your long term goal
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SQL, Python coding …

Basic mathematical and resoning questions.

Q1. Tell me about your self
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Q2. Explain the recent project
Ans. 
Developed a predictive model for customer churn in a telecom company
• Collected and cleaned customer data including usage patterns and demographics

• Used machine learning algorithms such as logistic regression and random forest

• Evaluated model performance using metrics like accuracy and AUC-ROC curve
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Q3. What is the difference between random forest and decision tree
Ans. 
Random forest is an ensemble learning method that uses multiple decision trees to make predictions, while a decision tree is a single tree-like structure that makes decisions based on features.
• Random forest is a collection of decision trees that work together to make predictions.

• Decision tree is a single tree-like structure that makes decisions based on features.

• Random forest reduces overfitting by averaging the predic...read more
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Q4. What is cost function
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A cost function is a mathematical formula used to measure the cost of a particular decision or set of decisions.
• Cost function helps in evaluating the performance of a model by measuring how well it is able to predict the outcomes.

• It is used in optimization problems to find the best solution that minimizes the cost.

• Examples include mean squared error in linear regression and cross-entropy loss in logistic regression.
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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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Topics like sql, python, aptitude were covered.

Q1. Questions from stats, machine learning were asked. Behavioral questions were also covered.
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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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