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Decision Point Senior Data Scientist Interview Questions and Answers

Updated 8 May 2023

Decision Point Senior Data Scientist Interview Experiences

1 interview found

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

I applied via Referral and was interviewed before May 2022. 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 - Coding Test 

Python, SQL and other languages were tested

Round 3 - Coding Test 

Various machine learning algorithms were tested

Round 4 - One-on-one 

(2 Questions)

  • Q1. Cultural round... General questions
  • Q2. What is your experience
  • Ans. 

    I have 5 years of experience in data science with expertise in machine learning and statistical analysis.

    • 5 years of experience in data science

    • Expertise in machine learning and statistical analysis

    • Worked on various projects involving data cleaning, feature engineering, and model building

    • Proficient in programming languages like Python and R

    • Experience in working with big data technologies like Hadoop and Spark

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Be well prepared with coding and be truthful

Senior Data Scientist Jobs at Decision Point

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Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. What friends think of you?
  • Ans. 

    My friends think of me as reliable, supportive, and always up for a good time.

    • Reliable - always there when they need help or support

    • Supportive - willing to listen and offer advice

    • Fun-loving - enjoys socializing and trying new things

  • Answered by AI

Interview Preparation Tips

Round: Resume Shortlist
Experience: After Resume Shortlist we had an aptitute round.
Tips: Answer according to your own judgement. Dont try to be too precise.

Round: HR Interview
Experience: I said they think I am a workaholic as I prefer to complete my work before chilling with them.

College Name: NIT Durgapur

Interview Preparation Tips

Round: HR Interview
Experience: Interview at 11 pm. Stressed environment, close to stress interview.
SELECTION PROCEDURE:
1.Online Test
2. GD
3. PI(HR)
GD TOPICS :
Topic 1 : How can education system benefit from interdisciplinary methods.
Topic 2 : Interconnected problems in the field of movie making.
INTERVIEW EXPERIENCE:
So you can speak German? Describe MS Dhoni in german. They opened Google Translate to counter check the words they wanted to be translated in both Deutsch and Spanish. Your profile speaks of an inclination towards software skills, why do you want to join an analytics company? Justify your action in two reasons as to why are you sitting here interviewing for the post of a data scientist rather than apply for a software engineer when this CV speaks highly of computer science? What is Finite Element Method? Explain. How relevant is your work in Computer Vision? Breakdown the tagline of Audi and translate accordingly. What is "Technik für Mobel" ? What are your current projects? Answer : Microsoft Xbox Kinect, Gesture Recognition. Counter question : But at Musimga you'd be doing far simpler stuff.? Counter suggestion : Why don't you go for MS?


Tips: Keep your cool during counter questions. Prepare your profile and CV well. Rest all is your hard work and groomed personal talents and acquired skills you learnt over the internet.

Skills: Ability To Cope Up With Stress, Spanish, German, Finite Element Modeling - FEM, Foreign Language
College Name: NIT Raipur
Funny Moments: Another HR enters in the midst of my interview and asks with bewildered amazement : What language is he speaking?
The other HR, "German".

Data Scientist Interview Questions & Answers

C5i user image Kushal Kulkarni

posted on 18 Jun 2024

Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I was interviewed in May 2024.

Round 1 - Assignment 

Questions based on ML,PYTHON, DATA VISUALIZATION

Round 2 - Technical 

(2 Questions)

  • Q1. What is TF-IDF IN NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document

    • TF-IDF is calculated by multiplying the term frequency (TF) by the inverse document frequency (IDF)

    • It helps in identifying the most important

  • Answered by AI
  • Q2. Python coding questions based on list

Interview Preparation Tips

Interview preparation tips for other job seekers - Practice python
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Assignment 

ML,DL,Python,NLP,Data VIsualization

Round 2 - Technical 

(1 Question)

  • Q1. Explain TF-IDF in NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency.

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document.

    • TF-IDF is calculated by multiplying the term frequency (TF) of a word by the inverse document frequency (IDF) of the word.

    • It helps in ident...

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed before Dec 2023. There were 3 interview rounds.

Round 1 - Coding Test 

Test of Basic data structures in Python include lists, tuples, and dictionaries, as well as loops and conditional statements.

Round 2 - Case Study 

Framework and requirements for chatbot implementation.

Round 3 - HR 

(1 Question)

  • Q1. Salary discussion

I applied via Recruitment Consultant and was interviewed in Dec 2018. There were 3 interview rounds.

Interview Questionnaire 

11 Questions

  • Q1. 1. Why Machine Learning?
  • Q2. 2. Why did you choose Data Science Field?
  • Ans. 

    I chose Data Science field because of its potential to solve complex problems and make a positive impact on society.

    • Fascination with data and its potential to drive insights

    • Desire to solve complex problems and make a positive impact on society

    • Opportunity to work with cutting-edge technology and tools

    • Ability to work in a variety of industries and domains

    • Examples: Predictive maintenance in manufacturing, fraud detection

  • Answered by AI
  • Q3. 3. What about Linear Regression? (Theory Part)
  • Q4. 4. What is the difference between Linear Regression and Logistic Regression?
  • Ans. 

    Linear Regression is used for predicting continuous numerical values, while Logistic Regression is used for predicting binary categorical values.

    • Linear Regression predicts a continuous output, while Logistic Regression predicts a binary output.

    • Linear Regression uses a linear equation to model the relationship between the independent and dependent variables, while Logistic Regression uses a logistic function.

    • Linear Regr...

  • Answered by AI
  • Q5. 5. Explain Confusion Matrix?
  • Ans. 

    Confusion matrix is a table used to evaluate the performance of a classification model.

    • It is a 2x2 matrix that shows the number of true positives, false positives, true negatives, and false negatives.

    • It helps in calculating various metrics like accuracy, precision, recall, and F1 score.

    • It is useful in identifying the strengths and weaknesses of a model and improving its performance.

    • Example: In a binary classification p...

  • Answered by AI
  • Q6. 6. Can we use confusion matrix in Linear Regression?
  • Ans. 

    No, confusion matrix is not used in Linear Regression.

    • Confusion matrix is used to evaluate classification models.

    • Linear Regression is a regression model, not a classification model.

    • Evaluation metrics for Linear Regression include R-squared, Mean Squared Error, etc.

  • Answered by AI
  • Q7. 7. Explain KNN Algorithm?
  • Ans. 

    KNN is a non-parametric algorithm used for classification and regression tasks.

    • KNN stands for K-Nearest Neighbors.

    • It works by finding the K closest data points to a given test point.

    • The class or value of the test point is then determined by the majority class or average value of the K neighbors.

    • KNN can be used for both classification and regression tasks.

    • It is a simple and easy-to-understand algorithm, but can be compu

  • Answered by AI
  • Q8. 8. Explain Random Forest and Decision Tree?
  • Ans. 

    Random Forest is an ensemble learning method that builds multiple decision trees and combines their outputs to improve accuracy.

    • Random Forest is a type of supervised learning algorithm used for classification and regression tasks.

    • It creates multiple decision trees and combines their outputs to make a final prediction.

    • Each decision tree is built using a random subset of features and data points to reduce overfitting.

    • Ran...

  • Answered by AI
  • Q9. 9. One Tricky Mathematical Question !
  • Q10. 10. What are the Projects you have done?
  • Ans. 

    I have worked on various projects involving data analysis, machine learning, and predictive modeling.

    • Developed a predictive model to forecast customer churn for a telecommunications company.

    • Built a recommendation system using collaborative filtering for an e-commerce platform.

    • Performed sentiment analysis on social media data to understand customer opinions and preferences.

    • Implemented a fraud detection system using anom...

  • Answered by AI
  • Q11. I didn't get shortlisted for 2nd Round.

Interview Preparation Tips

General Tips: anyone who wants to go in data science field should actually be interested in the field not the money. They should be good in Statistics, Probability and Theory part of ML algorithms.
They will ask you about the projects you have mentioned in resume and all the questions will be from that part.
Skills: Communication, Body Language, Problem Solving, Analytical Skills
Duration: 1-4 weeks

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via LinkedIn and was interviewed in Nov 2024. There were 2 interview rounds.

Round 1 - Coding Test 

There are 10 multiple-choice questions (MCQs) on Python, 20 MCQs on machine learning (ML), and 10 questions on deep learning (DL).

Round 2 - Technical 

(1 Question)

  • Q1. The technical round was divided in three phases - phase -1 : intro and professional projects They asked about the projects I have contributed in my full-time tenure. Then, asked me to pick any one of them...

I applied via Naukri.com and was interviewed in Apr 2022. There were 3 interview rounds.

Round 1 - Aptitude Test 
Round 2 - Coding Test 
Round 3 - Aptitude Test 

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare well on conditional probability , python basics, and your resume projects
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Campus Placement and was interviewed in Jul 2022. There were 4 interview rounds.

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 Resume tips
Round 2 - Aptitude Test 

Medium level of question are there in this section

Round 3 - Group Discussion 

Basic level of question are there in this section

Round 4 - Technical 

(2 Questions)

  • Q1. Q. What is joints? Q. What is linear search? Q. What is your hobby?
  • Ans. 

    Joints are connections between bones that allow movement and provide support to the body.

    • Joints are found throughout the body, such as the knee, elbow, and shoulder.

    • They are made up of bones, cartilage, ligaments, and synovial fluid.

    • Joints enable various types of movements, including flexion, extension, rotation, and abduction.

    • Different types of joints include hinge joints, ball-and-socket joints, and pivot joints.

    • Join...

  • Answered by AI
  • Q2. What is joints and what is your hobby?
  • Ans. 

    I'm not sure how joints relate to data science, but my hobby is playing guitar.

    • Joints can refer to the connection between two bones in the body or the way two things are connected or joined together.

    • Playing guitar is a hobby that helps me relax and unwind after a long day of working with data.

    • While seemingly unrelated to data science, playing an instrument can actually improve cognitive function and creativity, which c

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Basic SQL and Java language are enough for the interview

Skills evaluated in this interview

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Decision Point Interview FAQs

How many rounds are there in Decision Point Senior Data Scientist interview?
Decision Point interview process usually has 4 rounds. The most common rounds in the Decision Point interview process are Coding Test, Resume Shortlist and One-on-one Round.
How to prepare for Decision Point Senior 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 Decision Point. The most common topics and skills that interviewers at Decision Point expect are Machine Learning, Data Science, Python, SQL and Time Series Analysis.

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Decision Point Senior Data Scientist Interview Process

based on 1 interview

Interview experience

5
  
Excellent
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Decision Point Senior Data Scientist Salary
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₹14 L/yr - ₹25 L/yr
29% less than the average Senior Data Scientist Salary in India
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