Merkle Sokrati Data Science Manager Interview Questions and Answers

It was good more of maths

Q1. Behavioral questions
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Q2. Capacity planning , shrinkage, attrition, retention
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Q1. Build a MMX Model for the dataset given and share the insights
Ans. 
Build a MMX Model for a given dataset and share insights
• Preprocess the data by handling missing values and encoding categorical variables

• Split the data into training and testing sets

• Build the MMX model using appropriate algorithms like decision trees or random forests

• Evaluate the model using metrics like accuracy, precision, recall, and F1 score

• Interpret the model results to gain insights and make data-driven decisions
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Q2. How to evaluate Time series analysis
Ans. 
Time series analysis can be evaluated by examining the accuracy of forecasts, the model's ability to capture trends and patterns, and the overall performance metrics.
• Evaluate forecast accuracy using metrics like Mean Absolute Error (MAE) or Root Mean Squared Error (RMSE)

• Assess the model's ability to capture trends and patterns by visualizing the data and comparing it to the model's predictions

• Analyze the overall perfor...read more
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Q1. Profile Related
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Q2. Product management
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Reasoning and logic base qus

Q1. About metrics like Cpc, cvr
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Q1. Discuss about previous work
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Q1. Explain the projects worked on previous companies and questions related to it
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Q2. Questions bases on time series algorithms
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Q1. How do you handle conflict between resources
Ans. 
I encourage open communication and collaboration to resolve conflicts and find mutually beneficial solutions.
• Encourage open communication and active listening

• Identify the root cause of the conflict

• Brainstorm potential solutions together

• Find a mutually beneficial solution

• Document the resolution and follow up to ensure success
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Q2. What challenges you faced and what’s your contribution , how did you handle
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Q1. All questions were related to SQL and Context of the role
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Q2. Joins, Unions and case scenario
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