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Bright Data Solutions Jr. Data Scientist Interview Questions and Answers

Updated 7 Apr 2024

Bright Data Solutions Jr. Data Scientist Interview Experiences

1 interview found

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

(1 Question)

  • Q1. Tell me about your experience with SQL
  • Ans. 

    I have extensive experience with SQL, including writing complex queries, optimizing performance, and working with large datasets.

    • Proficient in writing complex SQL queries to extract and manipulate data

    • Experience with optimizing query performance through indexing and query tuning

    • Familiarity with working with large datasets and joining multiple tables

    • Knowledge of advanced SQL concepts such as window functions and common

  • Answered by AI
Round 2 - Technical 

(2 Questions)

  • Q1. What is R squared?
  • Ans. 

    R squared is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable.

    • R squared ranges from 0 to 1, with 1 indicating a perfect fit.

    • It is often used in regression analysis to evaluate the goodness of fit of a model.

    • An R squared value of 0.7 means that 70% of the variance in the dependent variable can be explained by the independent variabl

  • Answered by AI
  • Q2. How linear regression works?
  • Ans. 

    Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.

    • Linear regression finds the best-fitting straight line through the data points to predict the value of the dependent variable based on the independent variable(s).

    • It assumes a linear relationship between the variables and minimizes the sum of the squared differences between the obs...

  • Answered by AI

Skills evaluated in this interview

Interview questions from similar companies

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

Most like other campus recruiting test

Round 2 - Coding Test 

Coding for an example in python

Round 3 - One-on-one 

(2 Questions)

  • Q1. Query to print date in Sql
  • Ans. 

    Use SELECT statement with DATE_FORMAT function in SQL to print date in desired format.

    • Use SELECT DATE_FORMAT(date_column, 'desired_format') FROM table_name;

    • Replace 'date_column' with the column containing the date data and 'desired_format' with the format you want to print the date in.

    • Example: SELECT DATE_FORMAT(date_column, '%Y-%m-%d') FROM table_name;

  • Answered by AI
  • Q2. Question on list and tuple

Interview Preparation Tips

Interview preparation tips for other job seekers - Work hard on language and sql
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. What is precision and recall
  • Ans. 

    Precision and recall are evaluation metrics used in machine learning to measure the performance of a classification model.

    • Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

    • Recall is the ratio of correctly predicted positive observations to the all observations in actual class.

    • Precision is important when the cost of false positives is high, while recall is i...

  • Answered by AI

Skills evaluated in this interview

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

I applied via LinkedIn and was interviewed before Feb 2023. There were 2 interview rounds.

Round 1 - Technical 

(2 Questions)

  • Q1. What are the different supervised models used
  • Ans. 

    Supervised models include linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks.

    • Linear regression: used for predicting continuous outcomes

    • Logistic regression: used for binary classification

    • Decision trees: used for classification and regression tasks

    • Random forests: ensemble method using multiple decision trees

    • Support vector machines: used for classification ...

  • Answered by AI
  • Q2. Linear regression, logistic regression, decision tree
Round 2 - HR 

(1 Question)

  • Q1. What are the salary expectations

Skills evaluated in this interview

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

Do well and contribute well

Round 2 - Aptitude Test 

Do well and contribute well

Round 3 - Coding Test 

Do well and contribute well

Round 4 - One-on-one 

(2 Questions)

  • Q1. Why we choose this job
  • Q2. What are your expectations
Round 5 - HR 

(2 Questions)

  • Q1. Tell me about your self
  • Q2. What are your salary expectations
Round 1 - Aptitude Test 

It was an half hour test 20 questions purely based on ML and statistical knowledge.

Round 2 - Technical 

(1 Question)

  • Q1. ML techniques, statistics behind them and questions about your project

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare ML tecniques and algorithms and also the maths and statistics behind them
Interview experience
1
Bad
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Company Website and was interviewed in Sep 2023. 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 - Coding Test 

Normal there is not advance requirment

Round 3 - HR 

(5 Questions)

  • Q1. Will you work will less amount package
  • Q2. You wouldn't get any travel cost?
  • Q3. What about machine learning
  • Ans. 

    Machine learning is a branch of artificial intelligence that focuses on developing algorithms and models that can learn from and make predictions or decisions based on data.

    • Machine learning involves training algorithms to learn patterns from data and make predictions or decisions.

    • It can be supervised, unsupervised, or semi-supervised learning.

    • Examples include recommendation systems, image recognition, and natural langu

  • Answered by AI
  • Q4. Tellm me about any cloud platform
  • Ans. 

    A cloud platform is a service that allows users to store, manage, and process data remotely.

    • Cloud platforms provide scalable and flexible storage solutions

    • They offer various services such as computing power, databases, and analytics tools

    • Examples include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform

  • Answered by AI
  • Q5. Telll me about pointer
  • Ans. 

    A pointer is a variable that stores the memory address of another variable.

    • Pointers are used to access and manipulate memory directly.

    • They are commonly used in programming languages like C and C++.

    • Example: int *ptr; // declaring a pointer variable

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Nothing They will only look for people with less package.

Skills evaluated in this interview

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

Fibonacci series print

Round 2 - Assignment 

Sales dataset to predict future sales

Jr. Data Scientist Interview Questions & Answers

TCS user image prakhar makhija

posted on 13 Aug 2023

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Don’t add your photo or details such as gender, age, and address in your resume. These details do not add any value.
View all tips
Round 2 - Technical 

(1 Question)

  • Q1. Introduction and overview of the projects
Round 3 - Technical 

(1 Question)

  • Q1. Computer vision questions
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
-
Result
Not Selected

I applied via LinkedIn and was interviewed in Nov 2022. There were 2 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Properly align and format text in your resume. A recruiter will have to spend more time reading poorly aligned text, leading to high chances of rejection.
View all tips
Round 2 - One-on-one 

(3 Questions)

  • Q1. Evaluation metrics used in multiclass classification
  • Ans. 

    Evaluation metrics for multiclass classification

    • Accuracy

    • Precision

    • Recall

    • F1 Score

    • Confusion Matrix

  • Answered by AI
  • Q2. Difffereence between append and extend
  • Ans. 

    Append adds a single element to a list while extend adds multiple elements.

    • Append adds the element as it is to the end of the list.

    • Extend takes an iterable and adds each element of the iterable to the end of the list.

    • Append can be used to add a single element to a list.

    • Extend can be used to add multiple elements to a list.

    • Example: list1 = [1, 2, 3], list2 = [4, 5], list1.append(4) will result in [1, 2, 3, 4], list1.ext

  • Answered by AI
  • Q3. Sort a list and take out second minimum
  • Ans. 

    Sort a list and extract the second minimum value.

    • Sort the list in ascending order using the sort() method.

    • Extract the second minimum value using indexing.

    • Handle cases where the list has less than two elements.

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare python and ML basics with well defined projects with business use

Skills evaluated in this interview

Bright Data Solutions Interview FAQs

How many rounds are there in Bright Data Solutions Jr. Data Scientist interview?
Bright Data Solutions interview process usually has 2 rounds. The most common rounds in the Bright Data Solutions interview process are HR and Technical.
What are the top questions asked in Bright Data Solutions Jr. Data Scientist interview?

Some of the top questions asked at the Bright Data Solutions Jr. Data Scientist interview -

  1. Tell me about your experience with ...read more
  2. How linear regression wor...read more
  3. What is R squar...read more

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