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Tiger Analytics Interview Questions

Last Updated: Jan 02, 2024
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Tiger Analytics is a global analytics consulting firm that provides data-driven solutions to businesses in various industries such as healthcare, retail, financial services, and technology. The company was founded in 2011 and has its headquarters in the United States of America with offices in India and Singapore.

Tiger Analytics provides a range of services in the field of data management and analytics, including advanced analytics, data visualization, and consultancy services for data science. The company's solutions are designed to help clients make data-driven decisions, optimize their operations, and achieve their business goals. Some of the specific areas of expertise include customer analytics, supply chain analytics, marketing analytics, and risk analytics.

Tiger Analytics works with clients ranging from startups to Fortune 500 companies across various industries. The company has a team of over 800 professionals with expertise in data science, machine learning, artificial intelligence, and other advanced analytics techniques.

Tiger Analytics Recruitment Process

1. Eligibility Criteria

Depending on the position you are looking for, Tiger Analytics may have different eligibility requirements. But, in general, the following credentials and prerequisites apply:

Sr. No. Criteria Requirement
1. Educational Qualification Candidates for positions at Tiger Analytics normally need to hold a bachelor's or master's degree in a relevant subject, such as computer science, statistics, mathematics, engineering, or a related profession2
2. Technical Skills Applicants should be highly technical in areas like big data technologies like Hadoop, Spark, and Hive, as well as statistical modeling, machine learning, and Python, R, and SQL.
3. Work Experience Candidates with appropriate work expertise in analytics, data science, or related subjects are often sought after by the organization. Depending on the position level, varying amounts of work experience may be necessary.
4. Communication and Teamwork Good communication and collaboration skills are essential for working effectively in a team-oriented environment.
5. Problem-solving Skills Candidates should possess strong analytical and problem-solving skills, including the ability to identify and solve complex business problems.
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2. Interview Process

It is important to remember that based on the particular position and requirements of Tiger Analytics, the eligibility requirements may change. It is therefore advised to review the job description and get in touch with Tiger Analytics if you have any questions about the eligibility requirements.

Tiger Analytics has a multi-stage recruitment process to identify the best talent for their team. 

Candidates who successfully pass all the stages of the recruitment process are extended an offer to join the company.

Overall, Tiger Analytics places a strong emphasis on technical skills, problem-solving abilities, and cultural fit in its recruitment process. The company looks for candidates who are passionate about analytics and data science and are willing to take on challenging projects.

3. Interview Rounds

The process typically involves the following stages:

  • Online Application: Candidates can apply for job openings through the company's website or through job portals. The application process involves submitting a resume and cover letter.
  • Screening: The HR team reviews the applications and shortlists candidates based on their qualifications and experience. Shortlisted candidates are then invited for a phone or video screening interview.
  • Technical Assessment: Candidates who pass the screening stage are given a technical assessment test, which typically involves problem-solving exercises and questions related to data analytics and data science.
  • Technical Interview: Candidates who pass the technical assessment are invited for an in-person or virtual interview with the hiring manager or a member of the technical team. The interview focuses on the candidate's technical skills, experience, and problem-solving abilities.
  • Culture Fit Interview: Candidates who pass the technical interview are invited for a final round of interviews with the HR team and senior management. This interview assesses the candidate's fit with the company's culture, values, and work ethic.
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4. Roles offered by Tiger Analytics

Let's explore the different roles offered by Tiger Analytics before discussing their interview questions for freshers.

Tiger Analytics offers a variety of roles to professionals, including Data Analysts, Data Engineers, Database Administrators, Machine Learning Engineers, Data Scientists, and Data Architects.

  • Data Analysts are responsible for processing and visualizing data, running queries against databases, and developing and modifying algorithms to extract data from extensive datasets without compromising its quality.
  • Data Engineers develop and test scalable Big Data ecosystems for enterprises to enable data scientists to execute their algorithms on secure and highly optimized data platforms. They also upgrade or replace older versions of existing systems to increase database effectiveness.
  • Database Administrators ensure that all databases within an organization are functioning correctly and grant or revoke employee access to databases according to their needs. They also perform database backups and recoveries.
  • Machine Learning Engineers, in addition to having in-depth knowledge of powerful technologies such as SQL and REST APIs, perform A/B testing, build data pipelines, and implement standard machine learning algorithms like classification and clustering
  • Data Scientists analyze data to provide solutions to business challenges, conduct predictive research, comb through unstructured data, and spot trends and patterns to help businesses make better decisions.
  • Finally, Data Architects develop blueprints for data management, allowing for simple database integration, centralization, and best-practice security protection. They also ensure that the data engineers have the best equipment and setups to work with.

Tiger Analytics Technical Interview Questions: Freshers and Experienced

1. What is the difference between a primitive data type and an object?

Primitive data types are simple data types that are not composed of other data types. Examples of primitive data types include int, char, and boolean. On the other hand, an object is a complex data type that is composed of one or more primitive data types. An example of an object would be an ArrayList, which is composed of an array of ints.

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2. What are the eight primitive data types in Java?

The eight primitive data types in Java are byte, short, int, long, float, double, char, and boolean. These data types are used to store numeric values, character values, and boolean values.

3. How would you define a superclass?

A superclass, also known as a base class or parent class, is a class from which a subclass or child class is derived. For example, if the Student class is derived from the Person class, the Person class is considered the superclass. The superclass or base class is a class that serves as a parent to another class or class, such as the Bike class serving as a superclass to the Vehicle class.

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4. How do you convert a string to an integer in Java?

To convert a string to an integer in Java, you can use the parseInt() method of the Integer class. For example, to convert the string "123" to an integer, you can use the following code:

String str = "123";
int num = Integer.parseInt(str);

5. What is a constructor in Java?

A constructor is a special method in a Java class that is used to initialize the object's instance variables when the object is created. It has the same name as the class and no return type. Constructors can be overloaded, allowing you to create objects with different sets of initial values.

6. How do you handle exceptions in Java?

In Java, exceptions are handled using try-catch blocks. Code that may throw an exception is placed inside a try block, and any exceptions that are thrown are caught by one or more catch blocks. The catch blocks can handle the exception or rethrow it to be caught by another try-catch block. For example:

try {
  // code that may throw an exception
} catch (ExceptionType e) {
  // handle the exception
}

7. What is a package in Java?

A package in Java is a way of organizing related classes and interfaces into a single unit. Packages can be nested, and they provide a way to group related functionality together and prevent naming conflicts with classes and interfaces in other packages.

8. What is the difference between the equals() method and the == operator in Java?

The equals() method is a method of the Object class that is used to compare the contents of two objects for equality. The == operator, on the other hand, compares the memory addresses of two objects to determine if they are the same object. In other words, the == operator checks if two object references refer to the same object, while the equals() method checks if two objects have the same values.

9. What is the difference between a stack and a queue data structure, and when would you use each one?

A stack and a queue are two common data structures used in computer programming. 

  • Stack: A stack is a linear data structure in which elements are stored and accessed using a "last-in, first-out" (LIFO) approach. This means that the most recently added item is the first one to be removed. Stacks are used for tasks that require temporary storage of data, such as function calls, expression evaluation, or undo-redo operations. Some examples of applications that use stacks include web browsers (for the back button), compilers (for parsing expressions), and operating systems (for handling system calls).
  • Queue: A queue follows a "first-in, first-out" (FIFO) approach. This means that the first element added to the queue is the first one to be removed. Queues are commonly used in scenarios where you need to process items in the order they were received, such as printing jobs, message queues, or network requests. Some examples of applications that use queues include:
    • operating systems: for scheduling processes,
    • e-commerce websites: for order processing and
    • transportation systems: for handling passenger queues.

Therefore, stacks and queues are both useful data structures for managing collections of elements. If you need to process items in the order they were added, use a queue. If you need to handle items in reverse order, use a stack.

10. What is the purpose of version control, and what are some popular version control systems?

Version control is a system for managing changes to code or other documents over time. It allows us to keep track of various versions of our files, collaborate with others, and undo changes as needed.

Some popular version control systems include:

  1. Git: Git is a version control system that is widely used. Because Git is a distributed version control system, each developer has their own copy of the entire codebase.
  2. Subversion(SVN): SVN is a centralized version control system, all developers work on the same codebase.
  3. Mercurial: Mercurial is a distributed version control system, similar to Git. Mercurial is popular among developers who prefer a simpler, more streamlined workflow than Git.
  4. Perforce: Perforce is a centralized version control system for large teams and enterprise-level projects. Perforce includes sophisticated features such as fine-grained access control and asset management.

11. How do you handle missing or corrupted data in a dataset during the data cleaning process?

During the data cleaning process, missing or corrupted data can be a common problem. Here are a few ways to handle it:

  1. Remove the affected data: If only a small amount of data is missing or corrupted, it may be best to simply remove it from the dataset altogether.
  2. Replace with mean/median/mode: If a larger amount of data is missing, you can replace the missing values with the mean, median, or mode of the other data points in that column.
  3. Impute missing data: Imputation is a more advanced technique that involves using machine learning algorithms to predict what the missing data should be based on other features in the dataset. This method can be more accurate than simply replacing it with mean/median/mode, but it also requires more computational resources and may not always be appropriate depending on the nature of the missing data.
  4. Consult with a subject matter expert: If you're unsure of how to handle missing or corrupted data, it may be helpful to consult with someone who has expertise in the domain or field of study that the data relates to. They may be able to offer insights on how to interpret or handle the data in question.

It's important to note that the approach to handling missing or corrupted data will depend on the specific characteristics of the dataset and the goals of the analysis. It's always a good practice to carefully evaluate the data and consider multiple approaches to cleaning and preprocessing it before proceeding with any analysis.

12. Can you explain the concept of recursion in programming, and provide an example of a recursive function?

Recursion is a programming technique in which a function calls itself in order to solve a problem. The idea is to break down a problem into smaller sub-problems, and then solve each sub-problem by calling the function recursively until a base case is reached.

An example of a recursive function to calculate the factorial of a positive integer is:

def factorial(n):
    if n == 0:
        return 1
    else:
        return n * factorial(n-1)

In this function, we first check if the input n is equal to 0, which is our base case. If it is, we return 1 since the factorial of 0 is 1. Otherwise, we calculate the factorial of n-1 by calling the factorial function recursively and multiplying it by n to get the factorial of n.

For example, if we call factorial(5), the function will call itself with the input 4, then 3, then 2, then 1, until it reaches the base case of factorial(0). At this point, it will start returning the factorial of each number in the sequence, multiplying it by the next number until it reaches the final result of 120, which is the factorial of 5.

Recursive functions can be very powerful and can make complex problems easier to solve by breaking them down into smaller, more manageable sub-problems. However, it's important to make sure that the recursive function has a base case to avoid infinite recursion, which can cause the program to crash or hang.

13. How do you handle memory leaks in a software application?

Memory leaks occur when a program fails to release memory that is no longer needed and leads to a buildup of unused memory over time. This can cause the program to slow down or crash, and in extreme cases, it can cause the entire system to become unstable. Some of the ways to handle memory leaks in a software application are:

  1. Use a memory profiler: A memory profiler is a tool that helps to identify memory leaks by monitoring memory usage during program execution. It can show which objects are consuming the most memory and once the memory leak is identified, it can be fixed by updating the code accordingly.
  2. Free up memory when it is no longer needed: One of the most common causes of memory leaks is forgetting to free up memory when it is no longer needed. This can be done by explicitly deallocating memory using the "free" or "delete" functions in the code.
  3. Use smart pointers: Smart pointers are objects that manage memory allocation and deallocation automatically. They help to ensure that memory is always properly released, even in cases where the code may have unexpected errors or exceptions.
  4. Avoid circular references: Circular references occur when two or more objects reference each other, creating a loop that prevents them from being properly deallocated. To avoid this, it is important to design the code to use weak references or break the circular reference by introducing a third object to manage the relationship.
  5. Test the application thoroughly: Regular testing of the application can help to identify memory leaks early on. Automated testing tools can be used to simulate heavy usage scenarios and identify potential issues.

14. What is the difference between a synchronous and an asynchronous function in JavaScript?

S. No. Synchronous function Asynchronous function
1. Synchronous functions execute in a sequential manner blocking the execution of the program until the function has been completed. This means that any code following the synchronous function call will not be executed until the function has finished running. Asynchronous functions allow the program to continue executing while the function performs a time-consuming task in the background. The program does not wait for the function to complete, and any code following the function call is executed immediately. Once the time-consuming task is completed, the function executes its callback or resolves its promise with the result.
2. Although synchronous functions are simple to comprehend and debug, they might cause performance issues if they handle time-taking tasks like file system operations or network requests. Asynchronous functions are used usually for performing tasks that could cause the program to freeze or become unresponsive, for example, network requests or file system operations.

15. How do you approach debugging a complex software problem, and what tools do you use to aid in the process?

Debugging complex software problems is a challenging task, but a structured approach and the right tools can help make it more manageable. Some of the steps to take and tools to use when debugging a complex software problem are:

  1. Reproduce the problem: The first step is to reproduce the problem consistently. This involves identifying the specific steps that lead to the problem and ensuring that they can be reliably repeated.
  2. Gather information: Once the problem has been reproduced, information can be gathered about the error. This can include error messages, log files, and stack traces.
  3. Break the problem down: The problem can be broken down into smaller parts and isolate the issue. 
  4. Test hypotheses: Based on the information gathered, hypotheses are created about the cause of the problem and test them one by one to narrow down the possibilities.
  5. Use debugging tools: There are several tools available to aid in the debugging process, such as debuggers, profilers, and tracing tools. These can help to identify specific areas of the code that are causing the problem, track variables and their values, and identify performance bottlenecks.
  6. Collaborate with others: If the problem is particularly complex, it may be useful to collaborate with other developers or experts who may have more experience in the relevant areas.

16. Write a program to implement topoSort in the graph.

from collections import deque

def topoSort(graph):
    # calculate in-degree of each node
    in_degree = {node: 0 for node in graph}
    for node in graph:
        for neighbor in graph[node]:
            in_degree[neighbor] += 1
    
    # enqueue nodes with in-degree of 0
    queue = deque([node for node in graph if in_degree[node] == 0])
    topo_order = []
    
    # perform topological sort
    while queue:
        node = queue.popleft()
        topo_order.append(node)
        for neighbor in graph[node]:
            in_degree[neighbor] -= 1
            if in_degree[neighbor] == 0:
                queue.append(neighbor)
    
    # check for cycle
    if len(topo_order) != len(graph):
        raise ValueError("Graph contains cycle!")
    
    return topo_order

The topoSort function takes in a directed graph represented as a dictionary where each key is a node and the value is a set of neighbors. For example, the following graph can be represented as {'a': {'b', 'c'}, 'b': {'c', 'd'}, 'c': {'d'}, 'd': set()}:

  a --> b --> d
  |     |
  v     v
  c --> d

The implementation first calculates the in-degree of each node by iterating through the graph and counting the number of edges pointing into each node. Nodes with an in-degree of 0 are enqueued into a queue, which serves as the starting point for the topological sort. 

The topological sort is performed by dequeuing a node from the queue and appending it to the topo_order list. For each of the dequeued node's neighbors, the in-degree is decremented. If the neighbor's in-degree becomes 0, it is enqueued into the queue. 

This process is repeated until all nodes have been dequeued and added to the topo_order list. At the end of the function, the topo_order list is returned. If the length of the topo_order list does not match the number of nodes in the graph, it means that there is a cycle in the graph, so a ValueError is raised.

17. Write the program to reverse the string in java?

import java.util.Scanner;

public class ReverseString {
   public static void main(String[] args) {
        Scanner scanner = new Scanner(System.in);
        System.out.print("Enter a string to reverse: ");
        String str = scanner.nextLine();

        // Convert string to character array
        char[] charArray = str.toCharArray();

        // Reverse the character array
        for(int i = 0, j = charArray.length - 1; i < j; i++, j--) {
            char temp = charArray[i];
            charArray[i] = charArray[j];
            charArray[j] = temp;
        }

        // Convert character array back to string
        String reversedString = new String(charArray);

        System.out.println("Reversed string is: " + reversedString);
    }
}
  1. The user is prompted to enter a string to reverse.
  2. The toCharArray() method is used to convert the string to a character array.
  3. A loop is used to reverse the character array by swapping the first and last characters, then the second and second-to-last characters, and so on, until the middle of the array is reached.
  4. The reversed character array is converted back to a string using the String constructor that takes a char[] as an argument.
  5. The reversed string is printed to the console.

18. Can you have multiple init methods in a single Python class? If so, how do they work?

No, it is not possible to have multiple __init__ methods in a single Python class. The __init__ method is a special method that is called when an object of a class is created, and it is used to initialize the object's attributes.

If you define multiple __init__ methods in a class, Python will only recognize the last one defined, and the previous ones will be ignored. Attempting to call any of the ignored __init__ methods will raise a TypeError.

However, it is possible to simulate multiple __init__ methods by defining optional arguments and providing default values. For example, consider the following class:

class Person:
    def __init__(self, name, age, gender='Male', location='USA'):
        self.name = name
        self.age = age
        self.gender = gender
        self.location = location

In this example, we have defined a single __init__ method that takes four arguments: name, age, gender, and location. The gender and location arguments have default values of 'Male' and 'USA', respectively. This allows us to create objects of the Person class with different sets of attributes, depending on which arguments are provided.

19. What are B-trees Data structures?

In computer science and database systems, self-balancing search tree data structures known as B-trees are frequently employed. Large amounts of data can be stored and retrieved effectively with B-trees by reducing the number of disc accesses necessary to reach any given element.

An example of a multi-level index is a B-tree, which stores data in a hierarchical structure with a fraction of the data at each level. A defined number of keys and pointers are present in each node of the B-tree, and the keys are arranged to facilitate efficient searching and retrieval.

The degree, or the maximum number of offspring that each node can have, determines the structure of a B-tree. A B-tree of degree m has the following properties:

  1. Each node has at most m children.
  2. Each node, except for the root node, has at least ceil(m/2) children.
  3. The root node has at least 2 children.
  4. All leaves are at the same level.

B-trees are typically used in applications that require large amounts of data to be stored and accessed efficiently, such as database systems and file systems. B-trees are particularly well-suited to these applications because they minimize the number of disk accesses required to access any given element, which can significantly improve performance. B-trees are also self-balancing, which means that the structure of the tree is automatically adjusted as data is added or removed to ensure that the tree remains balanced and efficient.

20. How do you represent a graph in computer memory, and how does it affect the performance of Topological Sorting algorithm?

An adjacency matrix or an adjacency list are two methods that a graph can be stored in computer memory.

A 2D array known as an adjacency matrix is used to store connections between graph vertices. The values in the matrix show whether there is an edge between two vertices, while the rows and columns of the matrix stand in for vertices. The matrix can be implemented as a 2D array in memory, where the amount of memory used for each element is fixed. When applied to an adjacency matrix, Topological Sorting has an O(V^2) time complexity, where V is the number of vertices in the graph.

An adjacency list is a collection of linked lists used to store links between graph vertices. The edges related to one vertex are shown in each linked list. An array of linked lists in memory can be used to implement the adjacency list, with the amount of memory needed for each linked list inversely proportional to the number of edges connected to the vertex. Topological sorting on an adjacency list has a temporal complexity of O(V+E), where E is the number of edges in the graph.

The effectiveness of Topological Sorting algorithms can be impacted by the graph representation chosen. When the network is thick, an adjacency matrix is more effective because it requires a constant amount of time to determine if two vertices are connected by an edge.

However, for sparse graphs, an adjacency list is more efficient as it requires less memory and allows faster access to vertices and edges. Therefore, the choice of graph representation depends on the properties of the graph and the specific requirements of the Topological Sorting algorithm.

21. What is the difference between a HashMap and a TreeMap in Java?

HashMap and TreeMap are both implementations of the Map interface in Java, but they differ in their underlying data structures and performance characteristics.

Sr. No. HashMap TreeMap
1. HashMap is implemented using a hash table, which allows for constant-time (O(1)) access and insertion of elements, on average.  TreeMap, on the other hand, is implemented using a Red-Black Tree, which allows for logarithmic-time (O(log n)) access and insertion of elements. 
2. It is unordered and does not maintain any particular order of the keys. It maintains the keys in sorted order, which makes it useful for cases where the keys need to be accessed in a specific order. 
3. It provides the flexibility to store null values and null keys. TreeMap does not allow null keys, but it allows null values.

In summary, if the requirements include fast insertion and retrieval of elements without any specific order, and the ability to store null values and keys, then HashMap is the preferred choice. If the requirements include sorted key order and the ability to store null values, then TreeMap should be used. However, it is important to note that TreeMap may have a slower performance than HashMap in most cases due to its logarithmic time complexity.

22. What is the purpose of the 'self' keyword in Python class methods? Why is it important?

In Python, the self keyword is used in class methods to refer to the object instance on which the method is being called. When a class method is called on an object instance, the object instance is automatically passed to the method as the first argument, which is conventionally named self.

For example, consider the following class definition:

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def say_hello(self):
        print("Hello, my name is", self.name, "and I am", self.age, "years old.")

In this example, a new Person object is created by calling the __init__ function, and a greeting is printed using the say hello method. Both methods refer to the object instance that is being called on using the self keyword.

It's crucial to utilize the self keyword since it enables access to and modification of instance variables within class methods. It would not be allowed to refer to the object instance or its attributes inside the class methods without the self keyword.

Also, utilizing the self keyword clearly identifies the object instance being referenced in the method, reducing confusion and the likelihood of programming errors.

23. What is the difference between a shallow copy and a deep copy in Python? How do you create each one?

When making a copy of an object in Python, you have the option of making a shallow copy or a deep copy. The primary distinction between the two is that a deep copy makes a new object with a new memory address that contains a complete copy of the original object, whereas a shallow copy creates a new object with the same memory location as the original object.

To create a shallow copy of an object, you can use the copy() method or the slice operator [:]. For example:

original_list = [1, 2, [3, 4]]
shallow_copy = original_list.copy()
shallow_copy[2].append(5)

print(original_list)  # Output: [1, 2, [3, 4, 5]]
print(shallow_copy)   # Output: [1, 2, [3, 4, 5]]

In this example, the original_list contains a nested list. When we create a shallow copy of original_list using the copy() method, we get a new list object shallow_copy that points to the same memory location as original_list. When we modify the nested list in shallow_copy, the same modification is reflected in original_list, since both objects share the same memory location.

24. What is the difference between 'is' and '==' in Python? When should you use each one?

In Python, is and == are both comparison operators, but they have different functionalities.

The is operator checks whether two objects refer to the same object in memory, while the == operator checks whether two objects have the same value.

For example:

a = [1, 2, 3]
b = a
c = [1, 2, 3]

print(a is b)  # True, a and b refer to the same object in memory
print(a is c)  # False, a and c are different objects in memory
print(a == c)  # True, a and c have the same value

Therefore, you should use it when you want to check if two objects are the same object in memory, and you should use == when you want to check if two objects have the same value.

25. What is the difference between a module and a package in Python? How do you import them?

In Python, a module is a single file containing Python definitions, functions, and statements. A package is a collection of modules in a single directory, along with a special file called __init__.py that tells Python that the directory should be treated as a package.

To import a module or package in Python, you can use the import statement followed by the name of the module or package. For example:

import math  # imports the math module
from math import sqrt  # imports the sqrt function from the math module
import mypackage.mymodule  # imports the mymodule module from the mypackage package
from mypackage import mymodule  # imports the mymodule module from the mypackage package

When importing a package, you can specify which modules you want to import using the from ... import ... syntax, or you can use the import statement to import the entire package.

One important difference between modules and packages is that when you import a package, any code in the __init__.py file is executed. This can be useful for initializing variables or setting up the package's environment.

Tiger Analytics Interview Preparation

1. Interview Preparation Tips

Some interview preparation tips that may be helpful for preparing for an interview with Tiger Analytics are:

  1. Research the company: Before the interview, take time to learn about Tiger Analytics and its services, clients, and culture. Visit the company's website, social media pages, and news articles to get a better sense of the company's mission, values, and priorities.
  2. Review the job description: Carefully review the job description and make note of the required skills, qualifications, and responsibilities. Be prepared to discuss how your experience and skills match up with the requirements of the role.
  3. Practice your technical skills: Depending on the role you are applying for, you may be asked to complete a technical assessment or coding challenge. Practice your technical skills and review key concepts and algorithms relevant to the role.
  4. Prepare examples: Prepare examples of your past work experiences that demonstrate your skills and achievements relevant to the role. Use the STAR method (Situation, Task, Action, Result) to structure your responses and provide specific details.
  5. Prepare questions: Prepare a list of questions to ask during the interview. This can demonstrate your interest in the role and help you gain a better understanding of the company's expectations and culture.
  6. Dress appropriately: Dress professionally for the interview, whether it's conducted in person or virtually. Make sure your attire is appropriate for the company's dress code.
  7. Practice good communication: During the interview, practice good communication by speaking clearly and concisely. Be prepared to listen actively and respond thoughtfully to the interviewer's questions.

By following these tips and preparing thoroughly, you can increase your chances of success in the Tiger Analytics interview process.

Frequently Asked Questions

1. Is the Tiger Analytics interview tough?

Interviews can vary in difficulty depending on the company and position you are applying for. In general, analytics roles may require a strong foundation in statistics, data analysis, and data modelling. You may be asked to demonstrate your proficiency in these areas through technical questions, case studies, or practical exercises. Soft skills such as communication, problem-solving, and collaboration may also be evaluated.

To prepare for an analytics interview, it's a good idea to review your technical knowledge, practice your problem-solving skills, and be prepared to discuss your past experience and how it relates to the role. You may also want to research common interview questions for analytics roles and practice answering them.

Remember that the goal of the interview process is to determine if you are a good fit for the role and the company culture. So be yourself, be confident, and show that you are passionate about the work you do.

2. Does Tiger Analytics pay well?

Tiger Analytics pays its employees competitively with industry standards. The salary offered to an employee depends on several factors, including job role, level of experience, location, and other variables. It is best to research and compare salaries across different companies and industries before making any conclusions about a particular company's pay scale. The average Tiger Analytics salary ranges from ₹3.0 Lakhs/year for a Technical Writer to ₹51.7 Lakhs/year for a Director.

3. Is Tiger analytics a good company?

Tiger Analytics is a data analytics consulting company that offers services to companies in a variety of sectors, including e-commerce, healthcare, and finance. The business has won numerous honours and awards. In Glassdoor, Tiger Analytics has an overall rating of 4.1 out of 5, based on over 729 reviews left anonymously by employees. 83% of employees would recommend working at Tiger Analytics to a friend and 78% have a positive outlook for the business. The company has received multiple awards ranging from being recognized as a Leader by Forrester Research to being ranked among the fastest-growing tech companies by Inc. and Financial Times. The company consistently features in prestigious ‘Best Analytics Firms’ lists. 

Through a variety of training programs, hackathons, and knowledge-sharing sessions, Tiger Analytics places a high emphasis on the professional development of its employees and provides possibilities for both personal and professional development.

Yet, it's crucial to conduct your own research and assess the business in light of your personal priorities and values. When determining whether Tiger Analytics is a suitable fit for you, you may want to take into account aspects like the corporate culture, work-life balance, perks, and remuneration.

4. How long is the Tiger Analytics Interview process?

Depending on the position you're seeking and your degree of expertise, the time of the Tiger Analytics interview process can change. The interviewing procedure might often take a few weeks to a few months.

There are often numerous steps in the Tiger Analytics interview process, including a phone screening interview, a technical interview, and an in-person interview. There might also be further rounds of interviews in specific circumstances, such as a case study or a behavioural interview.

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