Dish Network Lead Data Scientist Interview Questions and Answers for Experienced

Q1. SQL joins and simple query
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Q2. Phython basics and simle data fram
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Q3. Hr round only formality
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Q1. Qualification of my degree
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Q2. My personal skills for company
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Q1. Good interview with no mistakes.
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Q2. Why you want to work with us ?
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I want to work with you because of your reputation in the industry and the exciting opportunities for growth and learning.
• I am impressed by your company's reputation in the industry and the positive feedback I have heard from current and former employees.

• Your organization offers a dynamic and challenging work environment, which aligns with my career goals and aspirations.

• I am excited about the opportunity to work with ...read more
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Q1. Current roles and responsibilities, Few queries to write, few questions related to DWH and what type of role you have done in past etc
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Q1. Managerial round mostly questions like what challenges did you face, how did you overcome on that, what was the major success / appreciation you got
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SQL query to find the top 5 employee having the max salary

Q1. If a dataset has missing values, how would you handle them?
Ans. 
I would handle missing values by imputing them using methods like mean, median, mode, or predictive modeling.
• Identify the extent of missing data in the dataset

• Consider the type of missing values (completely at random, missing at random, or not missing at random)

• Impute missing values using mean, median, mode, predictive modeling, or other statistical methods

• Evaluate the impact of imputation on the dataset's integrity an
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Q2. How would you analyze sales data to find ways to increase revenue?
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I would analyze sales data by identifying trends, customer behavior, and market opportunities to increase revenue.
• Identify key performance indicators (KPIs) such as average order value, conversion rate, and customer acquisition cost.

• Segment customers based on demographics, purchase history, and behavior to target specific groups with personalized marketing strategies.

• Analyze sales channels to determine which ones are m...read more
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Q1. Difference between joins
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Joins are used to combine rows from two or more tables based on a related column between them.
• Inner Join: Returns rows when there is a match in both tables.

• Left Join: Returns all rows from the left table and the matched rows from the right table.

• Right Join: Returns all rows from the right table and the matched rows from the left table.

• Full Outer Join: Returns rows when there is a match in one of the tables.

• Cross Join:
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Q2. Window function
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Q1. Write sql query in pythons
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Writing SQL queries in Python allows for seamless integration of data analysis and manipulation.
• Use libraries like pandas or sqlalchemy to execute SQL queries in Python

• Remember to establish a connection to the database before executing queries

• Utilize Python's flexibility to manipulate and analyze data retrieved from SQL queries
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