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Urban Company Senior Data Analyst Interview Questions, Process, and Tips

Updated 17 Mar 2022

Urban Company Senior Data Analyst Interview Experiences

1 interview found

I applied via Referral and was interviewed in Feb 2022. There were 5 interview rounds.

Round 1 - Assignment 

Given time series data of provider, compute hour wise provider wise no of seconds online

Round 2 - Technical 

(2 Questions)

  • Q1. Case study on the customer churn.
  • Q2. Questions on Probability and CLT
Round 3 - Technical 

(11 Questions)

  • Q1. What are assumptions in Linear Regression
  • Ans. 

    Assumptions in Linear Regression

    • Linear relationship between independent and dependent variables

    • Homoscedasticity (constant variance) of residuals

    • Independence of residuals

    • Normal distribution of residuals

    • No multicollinearity among independent variables

  • Answered by AI
  • Q2. What are overfitting and underfitting
  • Ans. 

    Overfitting and underfitting are two common problems in machine learning models.

    • Overfitting occurs when a model is too complex and fits the training data too closely, resulting in poor performance on new data.

    • Underfitting occurs when a model is too simple and cannot capture the underlying patterns in the data, resulting in poor performance on both training and new data.

    • Overfitting can be prevented by using regularizati...

  • Answered by AI
  • Q3. How do you improve the performance of Linear Regression
  • Ans. 

    To improve the performance of Linear Regression, you can consider feature engineering, regularization, and handling outliers.

    • Perform feature engineering to create new features that capture important information.

    • Apply regularization techniques like L1 or L2 regularization to prevent overfitting.

    • Handle outliers by either removing them or using robust regression techniques.

    • Check for multicollinearity among the independent...

  • Answered by AI
  • Q4. What are the metrics used to evaluate Linear Regression
  • Ans. 

    Metrics used to evaluate Linear Regression

    • Mean Squared Error (MSE)

    • Root Mean Squared Error (RMSE)

    • R-squared (R²)

    • Adjusted R-squared (Adj R²)

    • Mean Absolute Error (MAE)

    • Residual Sum of Squares (RSS)

    • Akaike Information Criterion (AIC)

    • Bayesian Information Criterion (BIC)

  • Answered by AI
  • Q5. What is Cost function and Error Function
  • Ans. 

    Cost function measures the difference between predicted and actual values. Error function measures the average of cost function.

    • Cost function is used to evaluate the performance of a machine learning model.

    • It measures the difference between predicted and actual values.

    • Error function is the average of cost function over the entire dataset.

    • It is used to optimize the parameters of the model.

    • Examples of cost functions are ...

  • Answered by AI
  • Q6. How do you handle Overfitting in Linear Regression
  • Ans. 

    Overfitting in Linear Regression can be handled by using regularization techniques.

    • Regularization techniques like Ridge regression and Lasso regression can help in reducing overfitting.

    • Cross-validation can be used to find the optimal regularization parameter.

    • Feature selection and dimensionality reduction techniques can also help in reducing overfitting.

    • Collecting more data can help in reducing overfitting by providing

  • Answered by AI
  • Q7. What is the difference between Least Squares Method and the maximum likelihood
  • Ans. 

    Least Squares Method and Maximum Likelihood are both used to estimate parameters, but differ in their approach.

    • Least Squares Method minimizes the sum of squared errors between the observed and predicted values.

    • Maximum Likelihood estimates the parameters that maximize the likelihood of observing the given data.

    • Least Squares Method assumes that the errors are normally distributed and independent.

    • Maximum Likelihood does n...

  • Answered by AI
  • Q8. What is the formula of Logistic Regression
  • Ans. 

    Logistic Regression formula is used to model the probability of a certain event occurring.

    • The formula is: P(Y=1) = e^(b0 + b1*X1 + b2*X2 + ... + bn*Xn) / (1 + e^(b0 + b1*X1 + b2*X2 + ... + bn*Xn))

    • Y is the dependent variable and X1, X2, ..., Xn are the independent variables

    • b0, b1, b2, ..., bn are the coefficients that need to be estimated

    • The formula is used to predict the probability of a binary outcome, such as whether...

  • Answered by AI
  • Q9. What is Type I and Type II error
  • Ans. 

    Type I error is rejecting a true null hypothesis, while Type II error is failing to reject a false null hypothesis.

    • Type I error is also known as a false positive

    • Type II error is also known as a false negative

    • Type I error occurs when the significance level is set too high

    • Type II error occurs when the significance level is set too low

    • Examples: Type I error - Convicting an innocent person, Type II error - Failing to convi...

  • Answered by AI
  • Q10. What metrics do you use to evaluate classification models
  • Ans. 

    Metrics used to evaluate classification models

    • Accuracy

    • Precision

    • Recall

    • F1 Score

    • ROC Curve

    • Confusion Matrix

  • Answered by AI
  • Q11. How do you handle overfitting and underfitting in Decision Trees
  • Ans. 

    Overfitting in decision trees can be handled by pruning, reducing tree depth, increasing dataset size, and using ensemble methods.

    • Prune the tree to remove unnecessary branches

    • Reduce tree depth to prevent overfitting

    • Increase dataset size to improve model generalization

    • Use ensemble methods like Random Forest to reduce overfitting

    • Underfitting can be handled by increasing tree depth, adding more features, and reducing regu...

  • Answered by AI
Round 4 - Case Study 

Case Study - How do you improve user engagement of Facebook?
Guesstimates - How many people watched the Squid Game series on Netflix

Round 5 - Case Study 

How do you reduce partner churn in UC?

Interview Preparation Tips

Topics to prepare for Urban Company Senior Data Analyst interview:
  • Machine Learning
  • Statistics
  • Case Studies
Interview preparation tips for other job seekers - Be thorough with Mathematics behind ML Algo, Practice Case Study Interviews.

Skills evaluated in this interview

Interview questions from similar companies

Data Analyst Interview Questions & Answers

Meesho user image vinay kalikota

posted on 2 Sep 2024

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

There are 2 coding challenges and 7 objective questions

Round 2 - Technical 

(1 Question)

  • Q1. Technical questions related to role
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Interviewer asked me basic SQL questions
  • Q2. In the second technical round he asked me advanced SQL topics (Windows Functions, Joins & Subqueries)
Round 2 - Coding Test 

In the second technical round interview asked me about advanced sql topics, theory questions and two coding questions in joins and window functions.

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Company Website and was interviewed before Feb 2023. There were 2 interview rounds.

Round 1 - Coding Test 

Simple SQL & Excel test

Round 2 - One-on-one 

(1 Question)

  • Q1. Will Face hiring Manager
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Company Website and was interviewed before Feb 2023. There was 1 interview round.

Round 1 - Technical 

(5 Questions)

  • Q1. SQL related questions like joins
  • Q2. Types of join in sql
  • Ans. 

    Types of join in SQL include inner join, left join, right join, and full outer join.

    • Inner join returns only the matching records from both tables.

    • Left join returns all records from the left table and the matching records from the right table.

    • Right join returns all records from the right table and the matching records from the left table.

    • Full outer join returns all records when there is a match in either the left or rig

  • Answered by AI
  • Q3. Practical use of left join
  • Ans. 

    A left join is used to combine data from two tables based on a common column, including all records from the left table.

    • Left join returns all rows from the left table and the matching rows from the right table.

    • It is useful when you want to retrieve all records from the left table, even if there are no matches in the right table.

    • The result of a left join will have NULL values in the columns from the right table where th...

  • Answered by AI
  • Q4. Number of rows after applying certain join operations
  • Ans. 

    The number of rows after applying join operations depends on the type of join used and the data in the tables being joined.

    • Inner join retains only the rows that have matching values in both tables

    • Left join retains all rows from the left table and the matched rows from the right table

    • Right join retains all rows from the right table and the matched rows from the left table

    • Full outer join retains all rows when there is a

  • Answered by AI
  • Q5. Difference between vlookup in excel and some function in sql
  • Ans. 

    VLOOKUP in Excel is used to search for a value in a table and return a corresponding value, while SQL functions like JOIN and WHERE are used to retrieve data from multiple tables based on specified conditions.

    • VLOOKUP is specific to Excel and works on a single table, while SQL functions can work on multiple tables.

    • VLOOKUP requires the table to be sorted in ascending order, while SQL functions do not have this requiremen...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare well for SQL

Skills evaluated in this interview

Interview experience
1
Bad
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Company Website and was interviewed in Apr 2024. There was 1 interview round.

Round 1 - Coding Test 

HackerRank Test - Python, SQL

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Aug 2023. There were 2 interview rounds.

Round 1 - Coding Test 

SQL query optimisation

Round 2 - HR 

(1 Question)

  • Q1. Regular discussion, about job role, why swiggy

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare excel, and sql
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Mar 2023. There were 2 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all Resume tips
Round 2 - HR 

(2 Questions)

  • Q1. What’s your previous experience
  • Ans. 

    I have 3 years of experience as a data analyst in the finance industry.

    • Worked with large datasets to extract meaningful insights

    • Performed data cleaning, transformation, and visualization

    • Created and maintained dashboards and reports for stakeholders

    • Conducted statistical analysis and built predictive models

    • Collaborated with cross-functional teams to identify business opportunities

  • Answered by AI
  • Q2. What’s your skills for the current role
  • Ans. 

    I have strong skills in data analysis, including proficiency in statistical analysis, data visualization, and programming languages such as Python and SQL.

    • Proficient in statistical analysis techniques

    • Skilled in data visualization using tools like Tableau

    • Strong programming skills in Python and SQL

    • Experience with data cleaning and preprocessing

    • Ability to interpret and communicate insights from data

    • Familiarity with machin...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Udaan Data Analyst interview:
  • SQL
  • Python
Interview preparation tips for other job seekers - Good to have python and sql skills and for data analyst these skills are must plus one visualisation tool
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
-

I applied via Job Portal and was interviewed before Jun 2022. There were 2 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all Resume tips
Round 2 - One-on-one 

(1 Question)

  • Q1. Previous company experience and current company roles and responsibilities
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Company Website and was interviewed in Jul 2023. There were 4 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all Resume tips
Round 2 - Aptitude Test 

Number sires, clock, logic, arithmetic, geometry

Round 3 - Coding Test 

Code test basic, ans the basic knowledge, write code

Round 4 - Technical 

(5 Questions)

  • Q1. What is python?
  • Ans. 

    Python is a high-level programming language known for its simplicity and readability.

    • Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.

    • It emphasizes code readability and uses indentation to define code blocks.

    • Python has a large standard library and a vibrant community of developers.

    • Example: print('Hello, World!')

    • Example: import pandas as pd

  • Answered by AI
  • Q2. What is python used for?
  • Ans. 

    Python is a versatile programming language used for data analysis, web development, artificial intelligence, automation, and more.

    • Data analysis and visualization

    • Web development (Django, Flask)

    • Artificial intelligence and machine learning (TensorFlow, PyTorch)

    • Automation and scripting

    • Scientific computing (NumPy, SciPy)

  • Answered by AI
  • Q3. What type of language is python?
  • Ans. 

    Python is a high-level programming language known for its simplicity and readability.

    • Python is an interpreted language, meaning it does not need to be compiled before running.

    • It supports multiple programming paradigms, including object-oriented, imperative, and functional programming.

    • Python has a large standard library and a thriving community, making it versatile and widely used.

    • Example: Python is used for web develop...

  • Answered by AI
  • Q4. What is oops in python?
  • Ans. 

    Object-oriented programming (OOP) is a programming paradigm based on the concept of 'objects', which can contain data and code.

    • OOP allows for the organization of code into reusable components called classes.

    • Classes can have attributes (variables) and methods (functions) associated with them.

    • In Python, everything is an object, and classes can be defined using the 'class' keyword.

    • Encapsulation, inheritance, and polymorph

  • Answered by AI
  • Q5. What is array in python?
  • Ans. 

    An array in Python is a data structure that stores a collection of elements of the same type.

    • Arrays can store elements such as integers, floats, or strings.

    • Arrays are indexed starting from 0, with elements accessed using their index.

    • Example: arr = ['apple', 'banana', 'cherry']

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Swiggy Data Analyst interview:
  • Advanced Excel
  • SQL Server
  • Python
Interview preparation tips for other job seekers - online interview

Skills evaluated in this interview

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Urban Company Interview FAQs

How many rounds are there in Urban Company Senior Data Analyst interview?
Urban Company interview process usually has 5 rounds. The most common rounds in the Urban Company interview process are Technical, Case Study and Assignment.
How to prepare for Urban Company Senior Data Analyst interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Urban Company. The most common topics and skills that interviewers at Urban Company expect are Python, SQL, Business Intelligence, Data Analysis and Data Science.
What are the top questions asked in Urban Company Senior Data Analyst interview?

Some of the top questions asked at the Urban Company Senior Data Analyst interview -

  1. What is the difference between Least Squares Method and the maximum likelih...read more
  2. How do you improve the performance of Linear Regress...read more
  3. What metrics do you use to evaluate classification mod...read more

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