Ford Business Solutions Data Scientist Interview Questions and Answers

Q1. Regression techniques
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Q2. Basic python codes
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Q1. Technical Project Related Questions
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Q1. Technical Project Related Questions
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Q1. Technical Project Related and Basics of Python and Data Science
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PYTHON,SQL,STATS,ML,DL

Q1. Strenght and weakness, long term and short term goal
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Technical and Code Snippet MCQs

Q1. Technical depending on which profile you are interviewing for. Some case studies as well.
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Q1. Situation based question, some technical as well.
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Q1. Behavioral, HR based questions.
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Q1. Tell me about yourself
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Q2. Questions from projects which was mentioned on resume
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Q1. Fitment based questions
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Q2. Explain a project
Ans. 
Developed a machine learning model to predict customer churn for a telecom company.
• Collected and cleaned customer data including usage patterns and demographics

• Used classification algorithms like Random Forest and Logistic Regression to build the model

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

Q1. Asked me about expected salary
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Q1. What is difference between lstm and rnn
Ans. 
LSTM is a type of RNN that addresses the vanishing gradient problem by using memory cells.
• RNN stands for Recurrent Neural Network, a type of neural network that processes sequential data.

• LSTM stands for Long Short-Term Memory, a type of RNN that includes memory cells to retain information over long sequences.

• LSTM is designed to overcome the vanishing gradient problem, which occurs when training RNNs on long sequences.

• L...read more
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Q1. What are different evaluation matrix ?
Ans. 
Evaluation matrices are used to assess the performance of models in data science.
• Confusion matrix: used to evaluate the performance of classification models.

• Precision, recall, and F1 score: measures for binary classification models.

• Mean squared error (MSE): evaluates the performance of regression models.

• R-squared: assesses the goodness of fit for regression models.

• Area under the ROC curve (AUC-ROC): evaluates the perfo...read more
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Q1. Mechanical engineering questions
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Q2. Some questions related to power bi and Excel
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Q1. Motivation come to this company
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Q2. Would like to be a contributor in automotive industry
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Q3. What experience in school
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Q4. How you understand data-driven bussiness
Ans. 
Data-driven business involves using data to make informed decisions and drive strategies.
• Using data to analyze trends and patterns in customer behavior

• Utilizing data to optimize marketing campaigns and target specific demographics

• Implementing data-driven decision-making processes to improve operational efficiency

• Leveraging data to forecast sales and inventory needs

• Measuring key performance indicators (KPIs) to track bu
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Q5. What your strength and weakness
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