i
Tiger Analytics
Filter interviews by
I applied via LinkedIn and was interviewed in Mar 2022. There were 4 interview rounds.
1. Coding Test Conducted on Hackereath.
There were 10 MCQ each carrying 10 marks.
2 programming questions (40pts, 60pts)
Question were based on DP and Segment Tree.
Implementing Python Collection Counter from Scratch
Create an empty dictionary to store the elements and their count
Iterate through the input list and add elements to the dictionary with their count
Return the dictionary
Example: input_list = ['apple', 'banana', 'apple', 'orange', 'banana']
Output: {'apple': 2, 'banana': 2, 'orange': 1}
Matrix multiplication, factorial and Fibonacci series implementation
Matrix multiplication involves multiplying two matrices to get a third matrix
Factorial is the product of all positive integers up to a given number
Fibonacci series is a sequence of numbers where each number is the sum of the two preceding ones
Factorial can be implemented using recursion or iteration
Fibonacci series can be implemented using recursion or
The probability of getting 5 Sundays in a 31 day month is less than 1%.
There are 7 days in a week, so the probability of any given day being a Sunday is 1/7.
In a 31 day month, there are 4 full weeks and 3 extra days.
The probability of the first 4 weeks having 4 Sundays is (1/7)^4.
The probability of the remaining 3 days being Sundays is (3/7).
Multiplying these probabilities gives a total probability of less than 1%.
Using Bayes Theorem, find the probability of getting 10 heads given 99 unbiased coins and 1 biased coin.
Identify the prior probability of getting 10 heads with unbiased coins
Calculate the likelihood of getting 10 heads with the biased coin
Use Bayes Theorem to calculate the posterior probability of getting 10 heads given the mix of coins
Consider the impact of the biased coin on the overall probability
Program to check if a number is power of 3
Use logarithm to check if the result is an integer
Check if the number is greater than 0
Check if the remainder is 0 when the number is divided by 3 repeatedly
Categorical features in Linear Regression require encoding using dummy variables. Removing one dummy variable avoids the dummy variable trap.
Categorical features need to be encoded using dummy variables to be used in Linear Regression
Dummy variable trap occurs when one dummy variable can be predicted from the others
Removing one dummy variable avoids the issue of multicollinearity and improves model performance
Example: ...
Probability of seeing a plane in 30 minutes given 15% chance in 10 minutes.
Calculate the probability of not seeing a plane in 10 minutes
Use the formula P(X>=1) = 1 - P(X=0)
Calculate the probability of not seeing a plane in 30 minutes using the above probability
Calculate the probability of seeing atleast 1 plane in 30 minutes using the formula P(X>=1) = 1 - P(X=0)
Probability of a random point in a circle of 1 unit radius being closer to the circumference than the center.
The probability is 1/4 or approximately 0.785.
This is because the area of the circle closer to the circumference is 1/4th of the total area.
This can be calculated using the formula for the area of a circle: A = πr^2.
I applied via Naukri.com and was interviewed in Sep 2024. There were 4 interview rounds.
Some questionaire was provided
MSE metric is commonly used in data analysis to measure the average squared difference between predicted values and actual values.
MSE helps to quantify the accuracy of a model by penalizing large errors more than small errors.
It is easy to interpret as it gives a clear measure of how well the model is performing.
MSE is differentiable, making it suitable for optimization algorithms like gradient descent.
Example: In line...
MSE metrics are commonly used to measure the average squared difference between predicted values and actual values in statistical analysis.
MSE helps in evaluating the performance of a predictive model by quantifying the accuracy of the model's predictions.
It penalizes large errors more heavily than small errors, making it a useful metric for identifying outliers or areas where the model is underperforming.
MSE is widely...
What people are saying about Tiger Analytics
I applied via Naukri.com and was interviewed in Aug 2023. There were 4 interview rounds.
Online Coding Assessment on HackerEarth
Tiger Analytics interview questions for designations
I was interviewed in Jul 2023.
Entropy is a measure of randomness or disorder in a system. Gini index is a measure of impurity in a dataset. Derivatives measure rate of change. P-value is the probability of observing a test statistic. Beta value is the coefficient in a regression model. Imbalanced datasets have unequal class distribution. Recall is the proportion of actual positives correctly identified. Precision is the proportion of predicted posi...
Get interview-ready with Top Tiger Analytics Interview Questions
I applied via Naukri.com and was interviewed in Dec 2023. There was 1 interview round.
Probability is the likelihood of a specific event occurring, expressed as a number between 0 and 1.
Probability ranges from 0 (impossible event) to 1 (certain event)
It can be calculated by dividing the number of favorable outcomes by the total number of possible outcomes
Probability can be represented as a percentage, fraction, or decimal
Python code to find the sum of all elements in a list
Use the sum() function to find the sum of all elements in a list
Ensure the list contains only numeric values for accurate results
I applied via Referral and was interviewed in Sep 2023. There were 4 interview rounds.
Hackerearth - python and ML stuff
I applied via Referral and was interviewed before Jan 2024. There were 3 interview rounds.
I applied via LinkedIn and was interviewed before Oct 2023. There were 3 interview rounds.
It was a 90-minute Aptitude + Coding test in which some LeetCode medium CP problems were asked.
Different regression models are used based on the type of data and relationship between variables.
Linear regression is used when there is a linear relationship between the independent and dependent variables.
Logistic regression is used when the dependent variable is binary.
Polynomial regression is used when the relationship between variables is non-linear.
Ridge regression is used when there is multicollinearity in the ...
R-squared is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable.
R-squared ranges from 0 to 1, with 1 indicating that all variance in the dependent variable is explained by the independent variable.
It is used in regression analysis to determine how well the regression line fits the data points.
A higher R-squared value indicates a bett...
I am a detail-oriented Senior Analyst with a passion for data analysis and problem-solving.
Experienced in conducting thorough research and interpreting complex data sets
Skilled in creating insightful reports and presentations for stakeholders
Proficient in using analytical tools such as Excel, SQL, and Tableau
I applied via Approached by Company and was interviewed before Oct 2023. There were 2 interview rounds.
Easy-medium maths coding questions
I have used various ML algorithms such as linear regression, decision trees, random forests, and neural networks in my projects.
Linear regression for predicting continuous values
Decision trees for classification and regression tasks
Random forests for ensemble learning and improved accuracy
Neural networks for complex pattern recognition
I applied via Referral and was interviewed before Oct 2023. There were 3 interview rounds.
It was basic questions to analyse the logic and problem solving approach. Nothing like complex data structures and algorithms.
Includes some basic mathematics questions (probability, permutation and combination, statistics, inferential statistics, hypothesis testing) and some data manipulation techniques using pandas and SQL (joins, filters, etc.)
Some of the top questions asked at the Tiger Analytics Senior Analyst interview -
The duration of Tiger Analytics Senior Analyst interview process can vary, but typically it takes about 2-4 weeks to complete.
based on 17 interviews
4 Interview rounds
based on 80 reviews
Rating in categories
Hyderabad / Secunderabad,
Chennai
+12-7 Yrs
Not Disclosed
Senior Analyst
497
salaries
| ₹8.5 L/yr - ₹18 L/yr |
Data Scientist
481
salaries
| ₹8.8 L/yr - ₹30 L/yr |
Data Engineer
468
salaries
| ₹7.8 L/yr - ₹28 L/yr |
Senior Software Engineer
376
salaries
| ₹8 L/yr - ₹19 L/yr |
Data Analyst
237
salaries
| ₹5.2 L/yr - ₹14 L/yr |
Fractal Analytics
Mu Sigma
LatentView Analytics
AbsolutData