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Tesco Data Scientist Interview Questions and Answers

Updated 6 Aug 2024

Tesco Data Scientist Interview Experiences

3 interviews found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Jul 2024. There was 1 interview round.

Round 1 - Coding Test 

Python and sql based questions

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed before Aug 2022. 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 tips
Round 2 - Technical 

(1 Question)

  • Q1. Heavy SQL solutions
Round 3 - Case Study 

Retail case study, with soft skills is required for this round

Interview Preparation Tips

Interview preparation tips for other job seekers - Make sure you're good in SQL. It will heavily revolve around SQL solving.

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I applied via Naukri.com and was interviewed in Nov 2021. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Round one was a combination of a technical round and a discussion on previous work experience. Questions - Previous work experience, Basic SQL questions, Basic Python questions, Basic Tableau question...
Round 2 - One-on-one 

(1 Question)

  • Q1. This was a culture fit round. This was a one on one discussion with the manager. Offer letter was rolled out after this round.

Interview Preparation Tips

Interview preparation tips for other job seekers - Cover your basics in SQL, Python, Tableau and ML.

Interview questions from similar companies

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed before Sep 2022. There were 6 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 tips
Round 2 - Technical 

(1 Question)

  • Q1. All the questiones were asked around CV. Mostly problems related to ML, DL, NLP, mathematics behind the algorithms, case studies, alternate solutions of popular use cases etc.
Round 3 - Technical 

(1 Question)

  • Q1. Same as round 1 but this round involved a lot of mathematical functions and derivations of several aspects of ML and DL. Also a lot of case studies were involved
Round 4 - Coding Test 

Had to share my screen and they gave live problems to test my knowledge in python

Round 5 - One-on-one 

(1 Question)

  • Q1. Call with hiring manager mostly on my CV and a lot of case studies.
Round 6 - HR 

(1 Question)

  • Q1. Typical HR round questions
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
More than 8 weeks
Result
Not Selected

I applied via LinkedIn and was interviewed in Oct 2023. There were 3 interview rounds.

Round 1 - HR 

(1 Question)

  • Q1. Why do you want to leave your current job?
Round 2 - Coding Test 

SQL coding question. Medium level

Round 3 - Case Study 

Explain my project and then case study regarding launching new apps

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed before Jun 2023. There were 3 interview rounds.

Round 1 - One-on-one 

(1 Question)

  • Q1. Resume related questions with the hiring manager
Round 2 - Coding Test 

Python for Data Science basics

Round 3 - Case Study 

Optimization case study

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

I applied via LinkedIn and was interviewed before May 2023. There were 4 interview rounds.

Round 1 - Technical 

(3 Questions)

  • Q1. Linear regression
  • Q2. Probability related questions
  • Q3. Sampling and AB testing
Round 2 - Technical 

(2 Questions)

  • Q1. Backpropagation in neural network
  • Ans. 

    Backpropagation is a method used to train neural networks by adjusting the weights based on the error in the output.

    • Backpropagation involves calculating the gradient of the loss function with respect to the weights of the network.

    • The gradient is then used to update the weights in the opposite direction to minimize the error.

    • This process is repeated iteratively until the network converges to a solution.

    • Backpropagation i...

  • Answered by AI
  • Q2. Clustering (k-means, DB scan)
Round 3 - Coding Test 

1 question on array (sorting related), 1 question on string (hard problem)

Round 4 - Behavioral 

(1 Question)

  • Q1. Behavioral questions
Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

3 Leet code mediums in 30 mins.

Round 2 - Technical 

(3 Questions)

  • Q1. 5 ML questions in 10 mins
  • Q2. 5 Stats question in 10 mins
  • Q3. 3 LC mediums in 30 minutes
  • Ans. 

    LC mediums refer to LeetCode mediums, which are medium difficulty coding problems on the LeetCode platform.

    • LC mediums are coding problems with medium difficulty level on LeetCode platform.

    • Solving 3 LC mediums in 30 minutes requires good problem-solving skills and efficient coding techniques.

    • Examples of LC mediums include 'Longest Substring Without Repeating Characters' and 'Container With Most Water'.

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Pray
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. How to reduce model inference latency
  • Ans. 

    To reduce model inference latency, optimize model architecture, use efficient algorithms, batch processing, and deploy on high-performance hardware.

    • Optimize model architecture by reducing complexity and removing unnecessary layers

    • Use efficient algorithms like XGBoost or LightGBM for faster predictions

    • Implement batch processing to make predictions in bulk rather than one at a time

    • Deploy the model on high-performance har

  • Answered by AI
  • Q2. Different sql joins and their difference
  • Ans. 

    SQL joins are used to combine rows from two or more tables based on a related column between them.

    • INNER JOIN: Returns rows when there is at least one match in both tables.

    • LEFT JOIN: Returns all rows from the left table and the matched rows from the right table.

    • RIGHT JOIN: Returns all rows from the right table and the matched rows from the left table.

    • FULL JOIN: Returns rows when there is a match in one of the tables.

    • SEL

  • Answered by AI

Skills evaluated in this interview

I was interviewed in Apr 2021.

Round 1 - Video Call 

(2 Questions)

Round duration - 60 Minutes
Round difficulty - Medium

I was asked two questions in this round . More emphasis was given on the theoretical aspect of the subject in this round .

  • Q1. How can you tune the hyperparameters of the XGBoost algorithm?
  • Ans. 

    Hyperparameters of XGBoost can be tuned using techniques like grid search, random search, and Bayesian optimization.

    • Use grid search to exhaustively search through a specified parameter grid

    • Utilize random search to randomly sample hyperparameters from a specified distribution

    • Apply Bayesian optimization to sequentially choose hyperparameters based on the outcomes of previous iterations

  • Answered by AI
  • Q2. Can you explain the hyperparameters in the XGBoost algorithm?
  • Ans. 

    Hyperparameters in XGBoost algorithm control the behavior of the model during training.

    • Hyperparameters include parameters like learning rate, max depth, number of trees, etc.

    • They are set before the training process and can greatly impact the model's performance.

    • Example: 'learning_rate': 0.1, 'max_depth': 5, 'n_estimators': 100

  • Answered by AI
Round 2 - Video Call 

(1 Question)

Round duration - 50 Minutes
Round difficulty - Medium

This round basically tested some fundamental concepts related to Machine Learning and proper ways to implement a model.

  • Q1. What is the difference between Ridge and LASSO regression?
  • Ans. 

    Ridge and LASSO regression are both regularization techniques used in linear regression to prevent overfitting by adding penalty terms to the cost function.

    • Ridge regression adds a penalty term equivalent to the square of the magnitude of coefficients (L2 regularization).

    • LASSO regression adds a penalty term equivalent to the absolute value of the magnitude of coefficients (L1 regularization).

    • Ridge regression tends to sh...

  • Answered by AI
Round 3 - Video Call 

(1 Question)

Round duration - 50 Minutes
Round difficulty - Medium

This round was based on some basic concepts revolving around Deep Learning .

  • Q1. What are outlier values and how do you treat them?
  • Ans. 

    Outlier values are data points that significantly differ from the rest of the data, potentially affecting the analysis.

    • Outliers can be identified using statistical methods like Z-score or IQR.

    • Treatment options include removing outliers, transforming the data, or using robust statistical methods.

    • Example: In a dataset of salaries, a value much higher or lower than the rest may be considered an outlier.

  • Answered by AI
Round 4 - HR 

(2 Questions)

Round duration - 30 Minutes
Round difficulty - Easy

This is a cultural fitment testing round .HR was very frank and asked standard questions. Then we discussed about my role.

  • Q1. What do you know about the company?
  • Q2. Why should we hire you?

Interview Preparation Tips

Eligibility criteriaAbove 3 years of experienceWalmart interview preparation:Topics to prepare for the interview - Statistics , SQL , Machine Learning Algorithms , Data Wrangling , Neural NetworksTime required to prepare for the interview - 3 monthsInterview preparation tips for other job seekers

Tip 1 : Must do Previously asked Interview as well as Online Test Questions.
Tip 2 : Do at-least 2 good projects and you must know every bit of them.

Application resume tips for other job seekers

Tip 1 : Have at-least 2 good projects explained in short with all important points covered.
Tip 2 : Every skill must be mentioned.
Tip 3 : Focus on skills, projects and experiences more.

Final outcome of the interviewSelected

Skills evaluated in this interview

Tesco Interview FAQs

How many rounds are there in Tesco Data Scientist interview?
Tesco interview process usually has 2 rounds. The most common rounds in the Tesco interview process are Technical, One-on-one Round and Resume Shortlist.
How to prepare for Tesco Data Scientist interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Tesco. The most common topics and skills that interviewers at Tesco expect are Python, Machine Learning, Recruitment, Analytical and Analytics.
What are the top questions asked in Tesco Data Scientist interview?

Some of the top questions asked at the Tesco Data Scientist interview -

  1. This was a culture fit round. This was a one on one discussion with the manager...read more
  2. Heavy SQL soluti...read more

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Tesco Data Scientist Interview Process

based on 2 interviews

Interview experience

4.5
  
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₹5.5 L/yr - ₹19.7 L/yr
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