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Jio Platforms Data Scientist Interview Questions, Process, and Tips

Updated 30 Dec 2024

Top Jio Platforms Data Scientist Interview Questions and Answers

Jio Platforms Data Scientist Interview Experiences

5 interviews found

Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Technical things
  • Q2. Llm model understanding how to implement
  • Ans. 

    Implementing a LLM model involves understanding its architecture and parameters.

    • Understand the architecture of the LLM model, which typically involves multiple layers of neurons.

    • Implement the model using a deep learning framework like TensorFlow or PyTorch.

    • Fine-tune the model by adjusting hyperparameters such as learning rate and batch size.

    • Train the model on a dataset with labeled examples to learn patterns and make p...

  • Answered by AI
Round 2 - HR 

(2 Questions)

  • Q1. Willing to relocate
  • Q2. Expected ctc, fixed variable

Interview Preparation Tips

Interview preparation tips for other job seekers - Interview was easy

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-

I appeared for an interview in Oct 2024.

Round 1 - Coding Test 

DATA MANUPULATION AND PTYON CODE

Data Scientist Interview Questions Asked at Other Companies

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Q4. Clone a Linked List with Random Pointers Given a linked list wher ... read more
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Q5. coding question of finding index of 2 nos. having total equal to ... read more
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Number of ways to reach nth stair

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - HR 

(1 Question)

  • Q1. Tell me about you

Jio Platforms interview questions for designations

 Data Science Intern

 (2)

 Data Engineer

 (5)

 Data Analyst

 (2)

 Big Data Engineer

 (1)

 Data Entry jobs

 (1)

I applied via Referral and was interviewed before Aug 2021. There was 1 interview round.

Round 1 - Technical 

(5 Questions)

  • Q1. Describe decision tree, xgboost, regression algorithms
  • Ans. 

    Decision tree, xgboost, and regression are machine learning algorithms used for prediction and classification tasks.

    • Decision tree is a tree-like model that splits data based on the most significant attribute to make predictions.

    • XGBoost is an optimized implementation of gradient boosting that uses decision trees as base learners.

    • Regression algorithms are used to predict continuous values based on input features, such as

  • Answered by AI
  • Q2. Describe loss function of deep learning.
  • Ans. 

    Loss function measures the difference between predicted and actual values.

    • It is used to optimize the model during training.

    • Common loss functions include mean squared error, binary cross-entropy, and categorical cross-entropy.

    • The choice of loss function depends on the problem being solved and the type of output.

    • The goal is to minimize the loss function to improve the accuracy of the model.

    • Loss function can be customized

  • Answered by AI
  • Q3. Describe project from start to end with challenges you faced and how you proposed solutions for those challenges.
  • Q4. Basic concept of any algorithm. Including intuition and assumptions.
  • Q5. Describe the latency of code and how to manage it.
  • Ans. 

    Latency refers to the time delay between a request and a response. It can be managed through various techniques.

    • Latency can be reduced by optimizing code and minimizing network calls.

    • Caching can also help reduce latency by storing frequently accessed data.

    • Load balancing and scaling can help distribute traffic and prevent bottlenecks.

    • Asynchronous programming can help improve performance by allowing multiple tasks to be ...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare according to your resume. Most of the questions would be around what you mentioned in your resume.

Skills evaluated in this interview

Interview questions from similar companies

I appeared for an interview before Jul 2021.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Model evaluation and performance metrices
  • Q2. Explaination of bagging and boosting techniques
  • Ans. 

    Bagging and boosting are ensemble techniques used to improve the accuracy of machine learning models.

    • Bagging involves training multiple models on different subsets of the training data and then combining their predictions through voting or averaging.

    • Boosting involves iteratively training models on the same data, with each subsequent model focusing on the samples that the previous models misclassified.

    • Bagging reduces va...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Work on basic concepts and previous projects

Skills evaluated in this interview

Interview Questionnaire 

1 Question

  • Q1. Diffe heilman algorithm
  • Ans. 

    Diffie-Hellman algorithm is a key exchange protocol used to securely exchange cryptographic keys over a public channel.

    • It is based on the concept of discrete logarithm problem.

    • It involves two parties, Alice and Bob, who generate their own private and public keys.

    • The public keys are exchanged and used to generate a shared secret key.

    • The shared secret key is used for encryption and decryption of messages.

    • It is widely use...

  • Answered by AI

Skills evaluated in this interview

I applied via Naukri.com and was interviewed before Jul 2021. There were 3 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. NLP and Computer Vision based Question were asked.
Round 2 - Technical 

(1 Question)

  • Q1. General Questions on Machine Learning and deployments technique
Round 3 - HR 

(1 Question)

  • Q1. Salary Negotiations and joining discussion

Interview Preparation Tips

Interview preparation tips for other job seekers - Interview questions are subject to current project requirements
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Referral and was interviewed in May 2024. There were 2 interview rounds.

Round 1 - One-on-one 

(2 Questions)

  • Q1. How to do model inference?
  • Ans. 

    Model inference is the process of using a trained machine learning model to make predictions on new data.

    • Load the trained model

    • Preprocess the new data in the same way as the training data

    • Feed the preprocessed data into the model to make predictions

    • Interpret the model's output to make decisions or take actions

  • Answered by AI
  • Q2. How to optimize spark query?
  • Ans. 

    Optimizing Spark queries involves tuning configurations, partitioning data, using appropriate data formats, and caching intermediate results.

    • Tune Spark configurations for memory, cores, and parallelism

    • Partition data to distribute workload evenly

    • Use appropriate data formats like Parquet for efficient storage and retrieval

    • Cache intermediate results to avoid recomputation

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

(2 Questions)

  • Q1. Have you used GEN AI?
  • Ans. 

    No, I have not used GEN AI in my work as a Data Scientist.

    • I have not used GEN AI in any of my projects or analyses.

    • I am not familiar with GEN AI and its capabilities.

    • I have not had the opportunity to work with GEN AI in any capacity.

  • Answered by AI
  • Q2. How do you take your solution to production?
  • Ans. 

    I take my solution to production by following a structured process involving testing, deployment, monitoring, and maintenance.

    • Develop a robust testing strategy to ensure the solution performs as expected in a production environment

    • Use continuous integration and continuous deployment (CI/CD) pipelines to automate the deployment process

    • Implement monitoring tools to track the performance of the solution in real-time and a...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Nagarro Data Scientist interview:
  • Basic Machine Learning

Skills evaluated in this interview

I applied via Job Portal and was interviewed before Jan 2021. There was 1 interview round.

Interview Questionnaire 

3 Questions

  • Q1. Dataset were give and asked to get an overview of data on IDE of your choice and then was asked to explain different steps required for solving classification problem w.r.t. shared data.
  • Q2. Was asked to explain my project and asked different data science techniques like dimensionality reduction, data cleaning approaches etc.. Was also asked to explain internals of algorithm used.
  • Q3. Knowledge of any cloud platform

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare for atleast 1 project which you have done thoroughly and know some basic python with pandas

Jio Platforms Interview FAQs

How many rounds are there in Jio Platforms Data Scientist interview?
Jio Platforms interview process usually has 1-2 rounds. The most common rounds in the Jio Platforms interview process are Technical, Coding Test and HR.
What are the top questions asked in Jio Platforms Data Scientist interview?

Some of the top questions asked at the Jio Platforms Data Scientist interview -

  1. Describe the latency of code and how to manage ...read more
  2. Describe decision tree, xgboost, regression algorit...read more
  3. Llm model understanding how to implem...read more

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Jio Platforms Data Scientist Interview Process

based on 5 interviews

Interview experience

3.2
  
Average
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Jio Platforms Data Scientist Salary
based on 118 salaries
₹5 L/yr - ₹20 L/yr
15% less than the average Data Scientist Salary in India
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Jio Platforms Data Scientist Reviews and Ratings

based on 23 reviews

3.8/5

Rating in categories

3.9

Skill development

4.5

Work-life balance

2.9

Salary

4.7

Job security

3.7

Company culture

2.6

Promotions

3.7

Work satisfaction

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