Tiger Analytics Data analyst Interview Questions & Experience Guide

Interview Preparation
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21

Company Name: Tiger Analytics

Position: Data Analyst

Application Process: The application process involved four rounds: an online test, a technical round, a combined behavioral and technical round, and an HR round. The interviewers were supportive, and the key was to speak confidently and align preparation with the role requirements.

Interview Rounds:

  • Round 1 - Online Test:

    • Questions Asked: The test included questions on data analysis, basic statistics, and problem-solving scenarios.
    • Your Approach: I focused on accuracy and time management, ensuring I understood each question before answering.
    • Outcome: Cleared the round successfully.

  • Round 2 - Technical Round:

    • Questions Asked: Questions covered SQL queries, data manipulation, and case studies related to data analysis.
    • Your Approach: I structured my answers logically, explaining my thought process clearly. For case studies, I broke down the problem into smaller parts.
    • Outcome: Advanced to the next round.

  • Round 3 - Behavioral + Technical Round:

    • Questions Asked: A mix of behavioral questions (e.g., teamwork, problem-solving) and technical questions (e.g., Python, data visualization).
    • Your Approach: I used the STAR method for behavioral questions and demonstrated my technical skills with practical examples.
    • Outcome: Passed this round as well.

  • Round 4 - HR Round:

    • Questions Asked: General HR questions about my background, career goals, and why I wanted to join Tiger Analytics.
    • Your Approach: I kept my answers concise and aligned them with the company’s values and the role.
    • Outcome: Received positive feedback and moved forward in the process.

Preparation Tips:

  • Brush up on SQL, Python, and basic statistics.
  • Practice case studies and problem-solving scenarios.
  • Prepare for behavioral questions using the STAR method.
  • Be confident and articulate during the interviews.

Conclusion:
The overall experience was smooth, and the interviewers were helpful. Speaking confidently and demonstrating a clear thought process were key. For future candidates, I’d recommend thorough preparation and staying calm during the interviews.

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Company Name: Tiger Analytics

Position: Data Analyst

Location: [Location not specified]

Application Process: The application was submitted online, and the interview process was conducted virtually.

Interview Rounds:

  • Round 1 - Technical Interview:
    • Questions Asked:
      • Basics of Statistics (e.g., mean, median, mode, standard deviation).
      • Python fundamentals (e.g., data structures, loops, functions).
      • SQL queries (e.g., joins, aggregations).
      • Simple coding problems (e.g., reversing a string, finding duplicates in a list).
    • Your Approach: I focused on explaining concepts clearly and writing clean, efficient code. For SQL, I made sure to structure my queries logically.
    • Outcome: The round went well, and I received positive feedback on my understanding of the basics.

Preparation Tips:

  • Brush up on fundamental statistics, Python, and SQL.
  • Practice coding problems on platforms like LeetCode or HackerRank.
  • Be prepared to explain your thought process clearly during the interview.

Conclusion:
The interview was straightforward, and the questions were aligned with the basics of the role. I felt confident in my responses, but I could have practiced more SQL scenarios to be even better prepared. Overall, it was a great learning experience!

23

Company Name: Tiger Analytics

Position: Data Analyst

Application Process: Applied through an online job portal. The process involved three stages: an assignment, a technical round, and a combined technical+HR round.

Interview Rounds:

  • Round 1 - Assignment:

    • Questions Asked: Given a dataset and asked to perform exploratory data analysis (EDA) and build a simple predictive model.
    • Your Approach: Started with basic data cleaning, followed by visualization to understand patterns. Built a simple linear regression model to predict the target variable.
    • Outcome: Cleared this round and moved to the next stage.

  • Round 2 - Technical Interview:

    • Questions Asked: Questions on machine learning concepts like overfitting, regularization, and model evaluation metrics. Also, detailed discussion on the assignment submitted.
    • Your Approach: Explained concepts with examples and linked them to the assignment work. Demonstrated understanding of trade-offs in model selection.
    • Outcome: Successfully cleared the technical round.

  • Round 3 - Technical + HR Interview:

    • Questions Asked: Technical questions on SQL and Python. HR questions about my projects, teamwork, and why I wanted to join Tiger Analytics.
    • Your Approach: Answered technical questions with code snippets where applicable. For HR, highlighted my passion for data analysis and how my skills align with the role.
    • Outcome: Cleared the final round and received an offer.

Preparation Tips:

  • Focus on machine learning basics, even if the role is for an analyst.
  • Be ready to explain your projects in detail.
  • Practice coding in Python and SQL, as they are often tested.

Conclusion:
The interview process was thorough but fair. The assignment round was a great way to showcase practical skills. I could have prepared more for the HR questions, but overall, it was a good learning experience. For future candidates, make sure to brush up on ML concepts and be confident in discussing your projects!

24

Company Name: Tiger Analytics

Position: Data Analyst

Application Process: The application process involved three rounds: a written test, a technical interview, and an HR interview. I applied through the company’s recruitment drive.

Interview Rounds:

  • Round 1 - Written Test:

    • Questions Asked: The written test consisted of aptitude questions and two coding problems.
    • Your Approach: I focused on solving the aptitude questions quickly to allocate more time to the coding problems. For the coding problems, I ensured I understood the problem statement clearly before writing the code.
    • Outcome: I passed this round and moved on to the technical interview.

  • Round 2 - Technical Interview:

    • Questions Asked: The interviewer asked basic programming questions on arrays and strings. They also inquired about my projects and internships mentioned in my resume.
    • Your Approach: I explained my thought process step-by-step for the coding questions and highlighted key aspects of my projects and internships.
    • Outcome: The interviewer seemed satisfied, and I advanced to the HR round.

  • Round 3 - HR Interview:

    • Questions Asked: This round focused on my background, career aspirations, and fit for the company culture.
    • Your Approach: I answered honestly and aligned my responses with the company’s values and goals.
    • Outcome: The HR round went well, and I received positive feedback.

Preparation Tips:

  • Practice coding problems on arrays and strings as they are commonly asked.
  • Be thorough with your resume, especially projects and internships, as they are likely to be discussed.
  • Brush up on aptitude topics to perform well in the written test.

Conclusion:
Overall, the interview process was smooth and well-structured. I felt prepared for the technical and HR rounds, but I could have practiced more coding problems to feel even more confident. My advice to future candidates is to focus on both technical skills and soft skills, as both are equally important in the selection process.