Citibank Big Data Engineer Interview Questions and Answers

Q1. Python coding questions
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Q1. Python moderate level coding questions
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Easy on cyber security

Q1. Introduce yourself this is
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Q2. What is your work experience
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Q1. Explain Sigmoid Function
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Sigmoid function is a mathematical function that maps any real value to a value between 0 and 1.
• Sigmoid function is commonly used in machine learning for binary classification problems.

• It is defined as f(x) = 1 / (1 + e^(-x)), where e is the base of the natural logarithm.

• The output of the sigmoid function is always in the range (0, 1).

• It is used to convert a continuous input into a probability value.

• Example: f(0) = 0.5
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Q2. What is a T-test in logistic regression
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A T-test in logistic regression is used to determine the significance of individual predictor variables.
• T-test in logistic regression is used to test the significance of individual coefficients of predictor variables.

• It helps in determining whether a particular predictor variable has a significant impact on the outcome variable.

• The null hypothesis in a T-test for logistic regression is that the coefficient of the predi...read more
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Q3. How to fit model to an unexplored market
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To fit a model to an unexplored market, conduct thorough market research, gather relevant data, identify key variables, test different models, and continuously iterate and refine the model.
• Conduct thorough market research to understand the dynamics of the unexplored market

• Gather relevant data on customer behavior, market trends, competition, etc.

• Identify key variables that may impact the market and model outcomes

• Test d...read more
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Q1. Load 60 GB of csv file and perform transformation.
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Use distributed computing framework like Apache Spark to efficiently load and transform the large CSV file.
• Use Apache Spark to distribute the workload across multiple nodes for faster processing.

• Utilize Spark's DataFrame API to read the CSV file and apply transformations.

• Consider partitioning the data to optimize performance.

• Use Spark SQL for complex transformations and aggregations.

• Leverage in-memory processing capabi
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Q1. Sql Queries were asked
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Q2. Was based on resume
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Q1. Based on resume the questions were
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Q2. Questions about family
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Python, sql was asked

Q1. Explain about how recommendation engine work
Ans. 
Recommendation engines analyze user data to suggest items based on preferences and behavior.
• Recommendation engines use collaborative filtering to suggest items based on user behavior and preferences.

• They can also use content-based filtering to recommend items similar to ones the user has liked in the past.

• Some recommendation engines combine both collaborative and content-based filtering for more accurate suggestions.

• Ex...read more
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