Data science has become a crucial field in modern businesses, including the aviation industry. Airlines like United Airlines harness the power of data science to optimize operations, improve customer experiences, and make informed business decisions. If you’re aspiring to join the data science team at United Airlines, here are some common interview questions and answers to help you prepare.
Table of Contents
Python Numpy, Pandas, and List Comprehension Interview Questions
Question: Explain what Python list comprehension is and provide an example.
Answer: Python list comprehension is a concise way to create lists. It allows you to create a new list by applying an expression to each item in an existing list. Here’s an example:
# Example: Create a list of squares of numbers from 1 to 10 using list comprehension squares = [x**2 for x in range(1, 11)] print(squares) # Output: [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
Question: What are the advantages of using list comprehension?
Answer:
- It is more concise and readable than traditional loops.
- It can be faster in execution compared to traditional loops for large datasets.
- It allows you to create lists with a single line of code.
Question: Can you nest list comprehensions in Python? Provide an example.
Answer: Yes, you can nest list comprehensions. Here’s an example:
# Example: Create a 2D matrix using nested list comprehension matrix = [[x*y for y in range(1, 4)] for x in range(1, 4)] print(matrix) # Output: [[1, 2, 3], [2, 4, 6], [3, 6, 9]]
Question: What is NumPy?
Answer: NumPy is a Python library used for numerical computing. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.
Question: How would you create a NumPy array from a Python list?
Answer: You can create a NumPy array from a Python list using numpy.array() function. Here’s an example:
import numpy as np # Create a NumPy array from a Python list
my_list = [1, 2, 3, 4, 5]
numpy_array = np.array(my_list)
print(numpy_array)
Question: Explain the difference between numpy.zeros() and numpy.ones() functions.
Answer:
numpy.zeros(shape) creates an array filled with zeros of the specified shape.
numpy.ones(shape) creates an array filled with ones of the specified shape.
Question: What is Pandas?
Answer: Pandas is a powerful Python library used for data manipulation and analysis. It provides data structures like DataFrame and Series that are designed for working with structured and time-series data.
Question: How would you read a CSV file into a Pandas DataFrame?
Answer: You can read a CSV file into a Pandas DataFrame using the pd.read_csv() function. Here’s an example:
import pandas as pd # Read a CSV file into a Pandas DataFrame df = pd.read_csv(‘file.csv’)
Question: Explain the difference between loc[] and iloc[] in Pandas.
Answer:
loc[] is label-based indexing, meaning you specify the name of the index.
iloc[] is integer-based indexing, meaning you specify the integer position of the data.
Here’s an example:
# Using loc[] df.loc[0] # Gets the row with label/index 0 # Using iloc[] df.iloc[0] # Gets the first row of the DataFrame
SQL Interview Questions
Question: What is SQL and what is its role in the context of databases?
Answer: SQL (Structured Query Language) is a standard language for managing and manipulating relational databases. It is used to perform tasks such as querying data, updating data, inserting new data, and deleting data in a relational database management system (RDBMS).
Question: Differentiate between INNER JOIN, LEFT JOIN, and RIGHT JOIN in SQL.
Answer:
- INNER JOIN: Returns records that have matching values in both tables.
- LEFT JOIN: Returns all records from the left table (table1), and the matched records from the right table (table2). The result is NULL from the right side, if there is no match.
- RIGHT JOIN: Returns all records from the right table (table2), and the matched records from the left table (table1). The result is NULL from the left side, when there is no match.
Question: Explain the difference between WHERE and HAVING in SQL.
Answer:
- WHERE: Used to filter rows before the data is grouped.
- HAVING: Used to filter groups after the data has been grouped.
Question: What is a subquery in SQL?
Answer: A subquery, also known as an inner query or nested query, is a query nested inside another query. It is used to return data that will be used in the main query as a condition.
Question: How do you find the second highest salary from an “Employee” table in SQL?
Answer: You can use a subquery to find the second highest salary. Here’s an example:
SELECT MAX(salary) AS second_highest_salary FROM Employee WHERE salary < (SELECT MAX(salary) FROM Employee);
Question: What is a primary key and a foreign key in SQL?
Answer:
- Primary Key: A primary key is a column or a set of columns that uniquely identifies each row in a table. It must contain unique values and cannot have NULL values.
- Foreign Key: A foreign key is a column or a set of columns in a table that is used to establish and enforce a link between data in two tables. It establishes a relationship between two tables and ensures referential integrity.
Question: Explain the GROUP BY clause in SQL.
Answer: The GROUP BY clause is used to group rows that have the same values into summary rows, like “find the number of customers in each city”. It is often used with aggregate functions (like COUNT(), SUM(), AVG(), etc.) to group the result set by one or more columns.
Question: What is the difference between TRUNCATE and DELETE in SQL?
Answer:
- TRUNCATE: Removes all rows from a table, but the table structure, its columns, constraints, and indexes remain. It is faster and cannot be rolled back.
- DELETE: Removes one or more rows from a table based on a condition. It is slower than TRUNCATE and can be rolled back.
Question: What does the INDEX keyword do in SQL?
Answer: An INDEX is used to create and retrieve data from the database very quickly. It is a performance tuning method to allow faster retrieval of records from the table.
Question: How can you find duplicate records in a table?
Answer: You can find duplicate records by using the GROUP BY clause and HAVING:
SELECT column1, column2, COUNT(*) FROM table_name GROUP BY column1, column2 HAVING COUNT(*) > 1;
Behavioral Interview Questions
Question: Tell me about a time when you had to manage multiple tasks or projects with tight deadlines. How did you prioritize your work?
Answer: “During my previous role, I was tasked with managing three projects simultaneously, each with its own deadlines. To prioritize effectively, I created a detailed project plan outlining the tasks and deadlines for each project. I then assessed the urgency and importance of each task, focusing on high-priority items first. I also communicated with stakeholders to manage expectations and adjust timelines when necessary. This approach helped me successfully complete all projects on time.”
Question: Describe a situation where you had to adapt to unexpected changes in your workload or schedule. How did you handle it?
Answer: “I once experienced a sudden increase in workload due to a team member’s unexpected absence. To adapt, I quickly reassessed my priorities and redistributed tasks among the team. I also identified tasks that could be postponed or delegated to ensure the critical work was completed on time. By staying flexible and maintaining open communication with my team, we were able to manage the workload effectively without compromising quality.”
Question: Can you share an example of a time when you successfully met a tight deadline under pressure?
Answer: “In my previous position, there was a project with a tight deadline due to unexpected delays in the initial phases. To ensure we met the deadline, I organized daily stand-up meetings with the team to track progress and identify any roadblocks. I also allocated specific tasks to team members based on their strengths and expertise. Despite the pressure, we maintained a positive and collaborative approach, which resulted in the successful completion of the project ahead of schedule.”
Question: How do you maintain your composure and focus during challenging or stressful situations at work?
Answer: “I have found that taking short breaks to clear my mind and refocus helps me maintain composure during stressful situations. I also practice deep breathing exercises and mindfulness techniques to stay calm and centered. Additionally, I prioritize tasks and create a structured plan to tackle the challenges one step at a time, which helps reduce overwhelming feelings.”
Question: Describe a time when you had to deal with a difficult or irate customer/passenger. How did you handle the situation?
Answer: “I encountered a situation where a passenger was upset due to a flight delay beyond our control. To address their concerns, I actively listened to their grievances, empathized with their frustration, and assured them that I would do everything possible to assist. I provided regular updates on the status of the flight and offered options for accommodations and rebooking. By remaining calm, patient, and maintaining a professional demeanor, I was able to de-escalate the situation and ensure the passenger felt heard and supported.”
Question: How do you prioritize self-care and manage work-life balance, especially during demanding periods?
Answer: “I believe in the importance of maintaining a healthy work-life balance to prevent burnout and manage stress effectively. During demanding periods, I make it a priority to set boundaries and allocate time for activities that recharge me, such as exercise, spending time with loved ones, and pursuing hobbies. I also communicate openly with my team about workload expectations and collaborate on strategies to maintain balance while meeting deadlines.”
Conclusion
Preparing for a data science interview at United Airlines or any similar company requires a solid understanding of key concepts and practical experience in applying data science techniques. The questions discussed in this blog post cover various aspects of data science, from the CRISP-DM process to handling imbalanced data and communicating results effectively. By familiarizing yourself with these questions and crafting thoughtful responses, you can confidently showcase your skills, problem-solving abilities, and enthusiasm for the field of data science. Remember, the goal is not just to answer questions but to demonstrate your capability to make meaningful contributions to data-driven decision-making in the dynamic world of aviation. Best of luck on your data science interview journey!
