United Airlines Senior Data Scientist Interview Questions and Answers

Data analysis , SQL, python, ML

Excellent performance

Q1. Tell me about your self
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Q2. Are you comfortable to position
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Two practical coding challenges will be followed by a multiple-choice section and then a system design task.

Develop an airline system that facilitates flight ticket booking.

Q1. What are the reasons for your interest in this position?
Ans. 
I'm excited about this position due to its alignment with my skills, growth opportunities, and the chance to contribute to impactful projects.
• Alignment with my expertise in software development, particularly in technologies like Java and cloud computing.

• Opportunities for professional growth, such as leading projects and mentoring junior developers.

• The company's commitment to innovation and its focus on developing solut...read more
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Q2. Can you describe a situation in which you encountered challenges and explain how you overcame them?
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Faced a critical deadline with a complex project; collaborated with the team to streamline processes and deliver on time.
• Identified bottlenecks in the development process, such as unclear requirements and lack of communication.

• Organized daily stand-up meetings to enhance team collaboration and ensure everyone was aligned on tasks.

• Implemented a task management tool to track progress and prioritize work effectively.

• Condu...read more
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Q1. What is the internal implementation of Hashing and what is collision?
Ans. 
Hashing is a technique used to map data to a fixed-size array, collision occurs when two different inputs produce the same hash value.
• Hashing involves using a hash function to map data to a fixed-size array.

• Collision happens when two different inputs produce the same hash value.

• Common techniques to handle collisions include chaining and open addressing.
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Q2. Is time complexity of HashMap always O(1) ?
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No, time complexity of HashMap is not always O(1).
• Time complexity of HashMap is O(1) on average, but can degrade to O(n) in worst case scenarios.

• Worst case scenarios include hash collisions, which can lead to linear probing and degrade performance.

• Load factor and capacity of the HashMap can also affect time complexity.

• In scenarios where many keys hash to the same index, the time complexity can degrade.
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Q1. Yet to have the interview. Ambition box is forcefully making me enter these details
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Q1. Common technical questions
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Q1. Advance Technical Questions based on your skill set taken by architect
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Common coding problems difficulty laver moderate

Q1. Common managerial question ,scenario base questions
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Q1. Asked about Projects ?
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Q2. Asked about algorithms
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Q1. Node js working in detail
Ans. 
Node.js is a runtime environment that allows you to run JavaScript on the server side.
• Node.js is built on Chrome's V8 JavaScript engine.

• It uses an event-driven, non-blocking I/O model that makes it lightweight and efficient.

• Node.js is commonly used for building server-side applications, APIs, and real-time applications.

• It has a large ecosystem of libraries and frameworks, such as Express.js and Socket.io.
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Q2. Timer working in node
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In Node.js, timers can be implemented using functions like setTimeout() and setInterval().
• Use setTimeout() to execute a function once after a specified delay

• Use setInterval() to execute a function repeatedly at a specified interval

• Clear a timer using clearTimeout() or clearInterval()

• Example: setTimeout(() => { console.log('Timer executed!'); }, 2000);
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Q1. HLD questions on db and backend
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Q2. Relational non relational db
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Q1. Asked about the project
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Q1. Picks one of the Projects to discuss the structure and methodology.
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Q2. Reverse a String
Ans. 
Reverse a given string
• Use built-in functions like reverse() or slice() in Python

• Iterate through the string in reverse order and append characters to a new string

• Convert the string to an array of characters, reverse the array, and join it back into a string
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Q3. Basic ML Questions about Resume Projects
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Q4. What is Regularization?
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Regularization is a technique used to prevent overfitting in machine learning models by adding a penalty term to the loss function.
• Regularization helps to reduce the complexity of the model by penalizing large coefficients.

• It adds a penalty term to the loss function, such as L1 (Lasso) or L2 (Ridge) regularization.

• Regularization helps to improve the generalization of the model by discouraging overfitting.

• Examples of re...read more
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Q5. Basics about Forescasting.
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