Infosys Data Scientist Interview Questions & Experience Guide

Interview Preparation
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Infosys Data Scientist Interview Questions & Experience Guide

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Company Name: Infosys

Position: Data Scientist

Location: [Not specified]

Application Process: I applied through the company website and was interviewed in March 2022.

Interview Rounds:

  • Round 1 - Resume Shortlist:

  • Questions Asked: None (resume screening).

  • Your Approach: Ensured my resume was crisp and highlighted relevant skills.

  • Outcome: Passed to the next round.

  • Round 2 - HR Round:

  • Questions Asked: Discussed the job role and confirmed the schedule for the technical round.

  • Your Approach: Stayed professional and clear about my expectations.

  • Outcome: Received confirmation for the technical round.

  • Round 3 - Technical Round:

  • Questions Asked: Technical questions related to data science.

  • Your Approach: Started strong but got stuck on some questions.

  • Outcome: Did not proceed further in the process.

Preparation Tips:

  • Focus on Python, SQL, Data Science, and Machine Learning topics.
  • Practice problem-solving and technical concepts thoroughly.
  • Apply to Infosys if you aim for a multinational company experience.

Conclusion:
The interview process was structured, and the initial rounds went well. However, I struggled in the technical round, which was a learning experience. For future candidates, I recommend thorough preparation in technical skills and staying calm under pressure.

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Company Name: Infosys

Position: Data Scientist

Application Process: Applied through campus placement.

Interview Rounds:

  • Round 1 - Technical Interview:

    • Questions Asked:

      1. Complete introduction.
      2. Detailed discussion about ML/DL projects (end-to-end).
      3. How to select a particular ML algorithm and why?
      4. Questions on Random Forest and XGBoost algorithms.
      5. Classification performance metrics in depth.
      6. How data validation was performed.
      7. Handling imbalanced datasets.
      8. Project deployment process.
      9. Basics of MLOps.
      10. Basic questions about deep learning algorithms (ANN, RNN, LSTM, CNN).
      11. In-depth discussion about previous work, from data collection to model deployment.
      12. Problems faced during the project and how they were tackled.

    • Your Approach:

      • Prepared a clear and concise introduction.
      • Discussed projects in detail, focusing on the end-to-end pipeline.
      • Explained algorithm selection based on problem requirements and performance metrics.
      • Addressed data validation and imbalance handling techniques.
      • Described deployment steps and MLOps basics.
      • Highlighted challenges and solutions in previous projects.

    • Outcome: Cleared the technical round.

Preparation Tips:

  • Focus on end-to-end project explanations.
  • Revise key ML/DL algorithms and their applications.
  • Practice explaining performance metrics and data validation techniques.
  • Be ready to discuss deployment and MLOps basics.
  • Prepare to talk about challenges faced and how you resolved them.

Conclusion:
The interview was thorough and focused on practical aspects of data science. Being well-prepared with project details and theoretical concepts helped. Future candidates should emphasize hands-on experience and problem-solving skills.

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Company Name: Infosys

Position: Data Scientist

Location: Not specified

Application Process: Applied via LinkedIn in December 2021.

Interview Rounds:

  • Round 1 - Resume Shortlist:

    • Questions Asked: Resume screening to assess qualifications and experience.
    • Your Approach: Ensured resume was concise and highlighted relevant skills and projects.
    • Outcome: Passed to the next round.

  • Round 2 - Aptitude Test:

    • Questions Asked: Logical reasoning, numerical reasoning, and verbal reasoning questions.
    • Your Approach: Focused on time management and accuracy while solving the problems.
    • Outcome: Cleared the aptitude test.

  • Round 3 - Group Discussion:

    • Questions Asked: Topics related to general awareness and current affairs.
    • Your Approach: Initiated the discussion with a thought-provoking question and actively participated.
    • Outcome: Successfully led the discussion and moved forward in the process.

Preparation Tips:

  • Remain professional throughout the interview process.
  • Clearly articulate your strengths and reasons for wanting the job.
  • Address potential concerns the interviewer might have about your profile.

Conclusion:
The interview process was structured and tested various skills, from logical reasoning to communication. Preparing thoroughly for each round and staying confident were key to my success. For future candidates, focus on showcasing your analytical and problem-solving abilities, and practice group discussions to stand out.

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Company Name: Infosys

Position: Data Scientist

Location: [Not specified]

Application Process: Applied via Naukri.com and was interviewed in June 2022.

Interview Rounds:

  • Round 1 - Resume Shortlist:

    • Questions Asked: Resume screening to assess qualifications and experience.
    • Your Approach: Ensured the resume was professional and highlighted relevant skills in data science and machine learning.
    • Outcome: Successfully shortlisted for the next round.

  • Round 2 - Aptitude Test:

    • Questions Asked: Focused on machine learning, artificial intelligence, and problem-solving in data.
    • Your Approach: Prepared by reviewing core concepts in data science and practiced problem-solving.
    • Outcome: Cleared the aptitude test.

Preparation Tips:

  • Focus on complex problem-solving in data.
  • Strong foundational knowledge in data science and machine learning is essential.
  • Practice sorting and analyzing data efficiently.

Conclusion:
The interview process was straightforward, with a focus on technical skills and problem-solving abilities. Ensuring a professional resume and thorough preparation in data science domains helped me succeed. For future candidates, I recommend emphasizing hands-on experience and problem-solving skills in your resume and interviews.

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Company Name: Infosys

Position: Data Scientist

Location: Not specified

Application Process: Applied via Naukri.com in May 2022.

Interview Rounds:

  • Round 1 - Resume Shortlist:

    • Questions Asked: None (resume screening).
    • Your Approach: Ensured my resume was error-free and highlighted relevant skills for the Data Scientist role.
    • Outcome: Passed to the next round.

  • Round 2 - HR Round:

    • Questions Asked:
      1. Tell me about yourself.
      2. Do you have any questions for me?
      3. Where do you want to see yourself in the future?
    • Your Approach:
      • Prepared a concise introduction focusing on my background, skills, and interest in data science.
      • Asked thoughtful questions about the company culture and growth opportunities.
      • Shared my career aspirations aligned with the role.
    • Outcome: Successfully cleared the HR round.

Preparation Tips:

  • Be confident and avoid stressing during the interview.
  • Double-check your resume for spelling or grammatical errors.
  • Prepare answers for common HR questions and have questions ready for the interviewer.

Conclusion:
The interview process was smooth, and the HR round was conversational. Being well-prepared and confident helped me perform well. For future candidates, focus on presenting a clear and concise resume, and practice common HR questions to build confidence.

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Company Name: Infosys

Position: Data Scientist

Application Process: I applied via a referral and was interviewed before June 2022.

Interview Rounds:

  • Round 1 - Resume Shortlist:

    • Outcome: My resume was shortlisted for further rounds.

  • Round 2 - Technical Round:

    • Questions Asked:
      1. Basics of KNN, Regression, R Squared, Batch normalization, and differences between LSTM and GRU.
      2. Questions on Padding.
    • Your Approach: I focused on explaining the concepts clearly and relating them to my past projects. For the project-related question, I described my current project in detail, highlighting my contributions.
    • Outcome: I successfully cleared this round.

  • Round 3 - HR Round:

    • Questions Asked:
      1. Describe your strengths and weaknesses.
      2. Why do you want to join Infosys?
    • Your Approach: I answered honestly, emphasizing my relevant strengths and how I work on my weaknesses. For the second question, I aligned my career goals with Infosys’s values and opportunities.
    • Outcome: I cleared the HR round and received a positive response.

Preparation Tips:

  • Prepare the basics of data science thoroughly.
  • Be well-versed in your past projects, as they are often discussed in detail.

Conclusion:
Overall, the interview process was smooth and well-structured. I felt confident because I had prepared the fundamentals well and could articulate my project experiences clearly. For future candidates, I recommend focusing on both technical concepts and soft skills to ace all rounds.

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Company Name: Infosys

Position: Data Scientist

Location: [Not specified]

Application Process: I applied via a referral and was interviewed in March 2021.

Interview Rounds:

  • Round 1 - Technical Interview:

    • Questions Asked:
      1. What is data science?
      2. What is Python and R?
    • Your Approach: I explained the fundamentals of data science, emphasizing its role in extracting insights from data. For Python and R, I highlighted their applications in data analysis and machine learning.
    • Outcome: Successfully cleared the round.

  • Round 2 - HR Interview:

    • Questions Asked: [Details not provided]
    • Your Approach: [Details not provided]
    • Outcome: [Details not provided]

  • Round 3 - Group Discussion:

    • Questions Asked: [Details not provided]
    • Your Approach: [Details not provided]
    • Outcome: [Details not provided]

  • Round 4 - [Round Type Not Specified]:

    • Questions Asked: [Details not provided]
    • Your Approach: [Details not provided]
    • Outcome: [Details not provided]

Preparation Tips:

  • Focus on understanding the basics of data science, including key concepts and tools like Python and R.
  • Practice explaining technical topics in simple terms for HR rounds.
  • Be prepared for group discussions by staying updated on current trends in data science.

Conclusion:
Overall, the interview process was thorough, and I found the technical round to be the most challenging yet rewarding. I would advise future candidates to strengthen their foundational knowledge and practice articulating their thoughts clearly.