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Tiger Analytics Machine Learning and Python Developer Interview Questions and Answers

Updated 20 Oct 2024

Tiger Analytics Machine Learning and Python Developer Interview Experiences

1 interview found

Interview experience
5
Excellent
Difficulty level
-
Process Duration
Less than 2 weeks
Result
Selected Selected
Round 1 - One-on-one 

(5 Questions)

  • Q1. Previous Projects
  • Q2. Technical Knowhow
  • Q3. Questions related to Model Deployment
  • Q4. Questions related to model training and optimization
  • Q5. ZQuestions related to Azure
Round 2 - Coding Test 

Some questions related to the File Handling, NLP Pipeline, Model Deployments

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Basic QA related Questions
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Recruitment Consulltant and was interviewed in Jun 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 - Technical 

(1 Question)

  • Q1. Python, Django questions Easy to Medium level DSA Discussion on Project and previous work experience Some SQL queries
Round 3 - Technical 

(1 Question)

  • Q1. Some Python questions and discussion on work experience Some design question like how you will design backend for some project from scratch Some managerial questions Questions on git
Round 4 - HR 

(1 Question)

  • Q1. Some basic HR questions

Interview Preparation Tips

Interview preparation tips for other job seekers - Be confident
Interview experience
2
Poor
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Job Portal and was interviewed in Mar 2024. There were 3 interview rounds.

Round 1 - Technical 

(2 Questions)

  • Q1. How to decide upon Spark cluster sizing?
  • Ans. 

    Spark cluster sizing depends on workload, data size, memory requirements, and processing speed.

    • Consider the size of the data being processed

    • Take into account the memory requirements of the Spark jobs

    • Factor in the processing speed needed for the workload

    • Scale the cluster based on the number of nodes and cores required

    • Monitor performance and adjust cluster size as needed

  • Answered by AI
  • Q2. Question on Spark internals
Round 2 - Case Study 

Implement a pipeline based on given conditions and data requirement

Round 3 - HR 

(1 Question)

  • Q1. There were no questions as such. They want me join on very next day when the HR discussion was over and started itimidating me with aggressive approach even without discussing the salary part and the benef...

Interview Preparation Tips

Interview preparation tips for other job seekers - I could clear both the rounds and salary discussion was the only thing left I decided not to join the company because of the way HR handled the process.
Based on the HR behaviour, I can say there is no respect for an employee/ candidate.
The behaviour was like as if I am at the mercy of the employer and I don't have any other company in this world.

Skills evaluated in this interview

I applied via Naukri.com and was interviewed in Sep 2021. There were 3 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 - Technical 

(1 Question)

  • Q1. 1. Types of cloud 2.Different Activity in ADF 3.Advance SQL 4.Basic OPPS concepts
  • Ans. 

    Questions related to cloud types, ADF activities, advanced SQL, and basic OOPs concepts.

    • Types of cloud include public, private, and hybrid

    • ADF activities include data ingestion, transformation, and loading

    • Advanced SQL includes window functions, subqueries, and joins

    • Basic OOPs concepts include encapsulation, inheritance, and polymorphism

  • Answered by AI
Round 3 - Behavioral 

(1 Question)

  • Q1. 1. Secenario bases case study. 2.Performance tuning in Datebases and warehouse. 3.SQL Logics

Interview Preparation Tips

Interview preparation tips for other job seekers - Be confident and and answer to the point as per knowledge and experience and understanding.
Talk about past work experiences

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed before Jan 2024. There were 3 interview rounds.

Round 1 - Coding Test 

Basics of SQL, Python

Round 2 - Coding Test 

Experience based questions, SQL and Python

Round 3 - One-on-one 

(2 Questions)

  • Q1. Tell me about the projects you worked on
  • Ans. 

    I have worked on projects involving building data pipelines, optimizing data storage, and developing machine learning models.

    • Built data pipelines using Apache Spark and Airflow

    • Optimized data storage by implementing partitioning and indexing strategies

    • Developed machine learning models for predictive analytics

  • Answered by AI
  • Q2. Based on experience some questions related to projects.
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Spark and airflow related questions
  • Q2. AWS services and it's related questions
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. NLP based question
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Sep 2023. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. SQL problems to solve nth highest salary
  • Ans. 

    Use SQL query with subquery to find nth highest salary

    • Use ORDER BY and LIMIT to get the nth highest salary

    • Use a subquery to exclude the top n-1 salaries before selecting the nth highest salary

  • Answered by AI
Round 2 - One-on-one 

(1 Question)

  • Q1. GCP big query Architecture

Skills evaluated in this interview

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

(4 Questions)

  • Q1. Components of Databricks
  • Ans. 

    Databricks is a unified data analytics platform that includes components like Databricks Workspace, Databricks Runtime, and Databricks Delta.

    • Databricks Workspace: Collaborative environment for data science and engineering teams.

    • Databricks Runtime: Optimized Apache Spark cluster for data processing.

    • Databricks Delta: Unified data management system for data lakes.

  • Answered by AI
  • Q2. How to read a json file
  • Ans. 

    To read a JSON file, use a programming language's built-in functions or libraries to parse the file and extract the data.

    • Use a programming language like Python, Java, or JavaScript to read the JSON file.

    • Import libraries like json in Python or json-simple in Java to parse the JSON data.

    • Use functions like json.load() in Python to load the JSON file and convert it into a dictionary or object.

    • Access the data in the JSON fi...

  • Answered by AI
  • Q3. Second highest salary SQL
  • Ans. 

    To find the second highest salary in SQL, use the MAX function with a subquery or the LIMIT clause.

    • Use the MAX function with a subquery to find the highest salary first, then use a WHERE clause to exclude it and find the second highest salary.

    • Alternatively, use the LIMIT clause to select the second highest salary directly.

    • Make sure to handle cases where there may be ties for the highest salary.

  • Answered by AI
  • Q4. How to configure the spark while creating the cluster
  • Ans. 

    Spark cluster configuration involves setting up memory, cores, and other parameters for optimal performance.

    • Specify the number of executors and executor memory

    • Set the number of cores per executor

    • Adjust the driver memory based on the application requirements

    • Configure shuffle partitions for efficient data processing

    • Enable dynamic allocation for better resource utilization

  • Answered by AI
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Tiger Analytics Interview FAQs

How many rounds are there in Tiger Analytics Machine Learning and Python Developer interview?
Tiger Analytics interview process usually has 2 rounds. The most common rounds in the Tiger Analytics interview process are One-on-one Round and Coding Test.
What are the top questions asked in Tiger Analytics Machine Learning and Python Developer interview?

Some of the top questions asked at the Tiger Analytics Machine Learning and Python Developer interview -

  1. Questions related to model training and optimizat...read more
  2. Questions related to Model Deploym...read more
  3. Technical Know...read more

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Tiger Analytics Machine Learning and Python Developer Interview Process

based on 1 interview

Interview experience

5
  
Excellent
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