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Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer Interview Questions, Process, and Tips

Updated 20 Aug 2024

Top Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer Interview Questions and Answers

Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer Interview Experiences

4 interviews found

Interview experience
1
Bad
Difficulty level
Moderate
Process Duration
More than 8 weeks
Result
No response

I applied via Approached by Company and was interviewed in Jul 2024. There were 2 interview rounds.

Round 1 - One-on-one 

(1 Question)

  • Q1. Tell me about yourself and the projects you have worked on so far?
  • Ans. 

    I am a data scientist and machine learning engineer with experience in developing predictive models for various industries.

    • Developed a predictive maintenance model for a manufacturing company to reduce downtime and maintenance costs.

    • Built a recommendation system for an e-commerce platform to personalize product recommendations for users.

    • Worked on a natural language processing project to classify customer reviews for se...

  • Answered by AI
Round 2 - Assignment 

NO RESPONSE AFTER SUBMITTING ASSIGNMENT

Interview Preparation Tips

Interview preparation tips for other job seekers - Please do not apply for this company. They do not care for the interviewees and also the interviewer are very rude and for 8 years of experienced person 5 years experienced person is assigned to take interview who can't even speak proper english
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(3 Questions)

  • Q1. Different scores for model evaluations, embedding models
  • Ans. 

    Different scores like accuracy, precision, recall, F1 for evaluating embedding models

    • Common evaluation metrics for embedding models include accuracy, precision, recall, and F1 score

    • Accuracy measures overall correctness of the model's predictions

    • Precision measures the proportion of true positive predictions among all positive predictions

    • Recall measures the proportion of true positive predictions among all actual positiv...

  • Answered by AI
  • Q2. How embedding models work
  • Ans. 

    Embedding models learn to represent words or entities as dense vectors in a continuous vector space.

    • Embedding models map words or entities to high-dimensional vectors where similar words have similar vectors.

    • These models are trained using neural networks to learn the relationships between words based on their context.

    • Popular embedding models include Word2Vec, GloVe, and FastText.

    • Embedding models are commonly used in na...

  • Answered by AI
  • Q3. What is difference between precision and recall
  • Ans. 

    Precision is the ratio of correctly predicted positive observations to the total predicted positive observations, while recall is the ratio of correctly predicted positive observations to the all observations in actual class.

    • Precision focuses on the accuracy of positive predictions, while recall focuses on the proportion of actual positives that were correctly identified.

    • Precision = TP / (TP + FP), Recall = TP / (TP + ...

  • Answered by AI
Round 2 - Technical 

(1 Question)

  • Q1. How word2vec works, how gensim works. what is tf-idf
  • Ans. 

    word2vec is a technique to create word embeddings, gensim is a Python library for topic modeling and similarity detection, tf-idf is a method to represent the importance of a word in a document.

    • word2vec is a neural network model that learns word embeddings by predicting the context of a word based on its surrounding words.

    • Gensim is a Python library for topic modeling, document similarity analysis, and other natural lan...

  • Answered by AI

Skills evaluated in this interview

Data Scientist and Machine Learning Engineer Interview Questions Asked at Other Companies

asked in EXL Service
Q1. What are supervised and unsupervised learning models?
asked in Wipro
Q2. What is your favourite algorithm and how have you implemented it?
Q3. how word2vec works, how gensim works. what is tf-idf
Q4. what is difference between precision and recall
Q5. different scores for model evaluations, embedding models
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
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 - One-on-one 

(2 Questions)

  • Q1. Gcp/aws expertise, traditional ml, mlops
  • Q2. K8, mlops, deep learning
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Recruitment Consulltant and was interviewed before Feb 2023. There were 3 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Q&A on ML and Deep Learning concepts
Round 2 - Technical 

(1 Question)

  • Q1. Exp related to pure Deep Learning questions
Round 3 - HR 

(1 Question)

  • Q1. Why was I leaving my previous company and general HR questions

Quantiphi Analytics Solutions Private Limited interview questions for designations

 Machine Learning Engineer

 (15)

 Machine Learning Engineer Intern

 (6)

 Senior Machine Learning Engineer

 (4)

 Data Scientist

 (2)

 Machine Learning Software Developer

 (1)

 Data Engineer

 (11)

 Senior Data Engineer

 (8)

 Big Data Engineer

 (1)

Interview questions from similar companies

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

(2 Questions)

  • Q1. Python question on list comprehension
  • Q2. Python related questions
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

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

Round 1 - Coding Test 

Focus more on python funda,ental and spark

Round 2 - Assignment 

They will ask more on datarbcisk related stuff

Interview Preparation Tips

Interview preparation tips for other job seekers - prepare well on python and prepare databricks adf and devops
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via LinkedIn and was interviewed in May 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 

It was 1 hour coding test with 2 questions. One was easy and another was medium level coding question.

Round 3 - Technical 

(3 Questions)

  • Q1. Few SQL Queries
  • Q2. Explain null hypothesis and p-value in terms of probability
  • Ans. 

    Null hypothesis is a statement that assumes no relationship or difference between variables. P-value is the probability of obtaining results as extreme as the observed data, assuming the null hypothesis is true.

    • Null hypothesis is a statement that assumes no effect or relationship between variables

    • P-value is the probability of obtaining results as extreme as the observed data, assuming the null hypothesis is true

    • Null hy...

  • Answered by AI
  • Q3. Explain Linear 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 models the relationship between a dependent variable and one or more independent variables using a linear equation.

    • Logistic regression models the probability of a binary outcome using a logistic function.

    • Linear regression is used for tasks like predicting hou...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Tiger Analytics Machine Learning Engineer interview:
  • SQL
  • Machine Learning
  • Data Science
  • Python
Interview preparation tips for other job seekers - Prepare for data science related questions and basic machine learning algorithms (Decision tree, PCA, etc.). Also prepare for SQL queries.

Skills evaluated in this interview

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

I applied via Naukri.com and was interviewed before Jun 2023. There was 1 interview round.

Round 1 - Coding Test 

4 technical questions, 1 python code, 2 SQL, 1 Spark

Interview Preparation Tips

Topics to prepare for Tiger Analytics Machine Learning Engineer interview:
  • Spark
  • SQL
  • Python
  • Hadoop
  • Hive
Interview preparation tips for other job seekers - Be confident and good in your skills

I was interviewed in Jun 2017.

Interview Questionnaire 

3 Questions

  • Q1. Tell me about about yourself?
  • Q2. Tell about your academic or your hands on projects in which you are involved?
  • Q3. Expected CTC?

Interview Preparation Tips

Round: Resume Shortlist
Experience: This round was "General Introduction Round" in which we have to introduce about our self-tell about hobbies and our family background and some lines about our hometown.
Tips: Just be confident and speak loudly and boldly.

Round: Test
Experience: It was online coding round via skype in which 5 questions were given out of which we have to do any 2.
Tips: "More you will practice more you will learn".
Duration: 20 minutes
Total Questions: 5

Round: Technical + HR Interview
Experience: This round was a combo with both technical and job questions. Questions were asked from my resume, basics questions in technical, general definitions and major questions from my project.
Tips: Specifically for Engineers searching for Data Scientist or Machine Learning based jobs, focus on your projects have done and do involve in the projects either on GitHub or haggle.
Clear your basic concepts and have a good knowledge of programming language like Python, R etc.

College Name: IIIT Bhubaneswar

Quantiphi Analytics Solutions Private Limited Interview FAQs

How many rounds are there in Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer interview?
Quantiphi Analytics Solutions Private Limited interview process usually has 2-3 rounds. The most common rounds in the Quantiphi Analytics Solutions Private Limited interview process are Technical, One-on-one Round and Resume Shortlist.
What are the top questions asked in Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer interview?

Some of the top questions asked at the Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer interview -

  1. how word2vec works, how gensim works. what is tf-...read more
  2. what is difference between precision and rec...read more
  3. different scores for model evaluations, embedding mod...read more

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Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer Interview Process

based on 4 interviews

Interview experience

3.5
  
Good
View more

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30% less than the average Data Scientist and Machine Learning Engineer Salary in India
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Quantiphi Analytics Solutions Private Limited Data Scientist and Machine Learning Engineer Reviews and Ratings

based on 4 reviews

3.7/5

Rating in categories

4.2

Skill development

3.9

Work-life balance

3.9

Salary

3.3

Job security

3.9

Company culture

3.4

Promotions

3.7

Work satisfaction

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