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Fractal Analytics Senior Data Scientist Interview Questions and Answers

Updated 12 Jan 2025

Fractal Analytics Senior Data Scientist Interview Experiences

4 interviews found

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

20 MCQ questions related to Data science and 1 coding ML question.

Round 2 - Technical 

(2 Questions)

  • Q1. What is overfitting and underfitting?
  • Ans. 

    Overfitting and underfitting are common problems in machine learning where a model performs too well on training data but poorly on unseen data, or performs poorly on both training and unseen data due to oversimplification.

    • Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern, leading to poor generalization on unseen data.

    • Underfitting happens when a model is too simple...

  • Answered by AI
  • Q2. What is K-fold CV?
  • Ans. 

    K-fold CV is a technique used to evaluate the performance of a machine learning model by splitting the data into k subsets.

    • Data is divided into k subsets, with one subset used as the validation set and the rest as training sets.

    • The process is repeated k times, with each subset used once as the validation data.

    • The average of the k validation results is used as the final performance metric.

    • Helps in reducing bias and vari...

  • 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 Referral and was interviewed in Jan 2024. There were 3 interview rounds.

Round 1 - Technical 

(2 Questions)

  • Q1. Initially asked to introduce myself and my work experience.
  • Q2. Based on my work experience, the panel asked further questions around my projects, going deeper into the basics of machine learning algorithms that I used for regression models and time series forecasting ...
Round 2 - One-on-one 

(1 Question)

  • Q1. The second round was more of like techno-managerial round where the panel asked me how I did my latest project, what were the obstacles faced, how did I overcome them, etc.
Round 3 - HR 

(1 Question)

  • Q1. The final round was with the HR where the salary negotiation part happened.

Interview Preparation Tips

Interview preparation tips for other job seekers - If you know the basics of machine learning and data science algorithms, this should be an easy - medium interview for you. You should expect cross questions against your CV and past projects.

Senior Data Scientist Interview Questions Asked at Other Companies

Q1. What is the difference between logistic and linear regression?
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Q5. How do you handle large amount of data in financial domain?
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 May 2023. There were 4 interview rounds.

Round 1 - Coding Test 

2 sections. First, multiple choice questions regarding Ml algo, SQl. Second, ML coding problem.

Round 2 - Technical 

(1 Question)

  • Q1. Details about dimensionality reductions, the difference between bagging and boosting techniques, details about XgBoost, and metrics to choose for the given Ml classification problem.
Round 3 - HR 

(1 Question)

  • Q1. Interview with HR manager, behavioural questions.
Round 4 - One-on-one 

(1 Question)

  • Q1. Interview with business leadership.

Interview Preparation Tips

Topics to prepare for Fractal Analytics Senior Data Scientist interview:
  • ML
  • regression, regularization
  • PCA
  • Boosting algorithms
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

The coding round was relatively easy. A sufficient amount of preparation on LeetCode should be beneficial, along with reviewing the sample questions.

Round 2 - Technical 

(2 Questions)

  • Q1. All theoretical questions about Linear Regression
  • Q2. Past projects

Fractal Analytics interview questions for designations

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 (19)

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 Senior Analytics Consultant

 (2)

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 (3)

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 Business Intelligence Consultant

 (1)

 Data Engineer

 (22)

 Data Analyst

 (4)

Interview questions from similar companies

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
Selected Selected
Round 1 - One-on-one 

(3 Questions)

  • Q1. What is Overfitting in decision tree
  • Ans. 

    Overfitting in decision trees occurs when the model learns noise in the training data rather than the underlying pattern.

    • Overfitting happens when the decision tree is too complex and captures noise in the training data.

    • It leads to poor generalization on unseen data, as the model is too specific to the training set.

    • To prevent overfitting, techniques like pruning, setting a minimum number of samples per leaf, or using en

  • Answered by AI
  • Q2. What is bagging
  • Ans. 

    Bagging is a machine learning ensemble technique where multiple models are trained on different subsets of the training data and their predictions are combined.

    • Bagging stands for Bootstrap Aggregating.

    • It helps reduce overfitting by combining the predictions of multiple models.

    • Random Forest is a popular algorithm that uses bagging by training multiple decision trees on random subsets of the data.

  • Answered by AI
  • Q3. What is neuron How its used in DL
  • Ans. 

    A neuron is a basic unit of a neural network that receives input, processes it, and produces an output.

    • Neurons are inspired by biological neurons in the human brain.

    • They receive input signals, apply weights to them, sum them up, and pass the result through an activation function.

    • Neurons are organized in layers in a neural network, with each layer performing specific tasks.

    • In deep learning, multiple layers of neurons ar...

  • Answered by AI

Skills evaluated in this interview

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 Aug 2024. There were 4 interview rounds.

Round 1 - Aptitude Test 

It was having basic aptitude questions

Round 2 - Communication 

(2 Questions)

  • Q1. They asked basic english question
  • Q2. And alos topic was provided so we had to speak on it.
Round 3 - Technical 

(2 Questions)

  • Q1. SQL syntax and difference between having and where clause
  • Ans. 

    HAVING clause is used with GROUP BY to filter grouped rows, WHERE clause is used to filter individual rows.

    • HAVING clause is used with GROUP BY to filter grouped rows based on aggregate functions

    • WHERE clause is used to filter individual rows based on conditions

    • HAVING clause is applied after GROUP BY, WHERE clause is applied before GROUP BY

    • HAVING clause can only be used with SELECT statement that contains a GROUP BY clau

  • Answered by AI
  • Q2. Difference between array and linkedlist,stack and queue
  • Ans. 

    Arrays store elements in contiguous memory, while linked lists use nodes with pointers. Stacks follow LIFO, queues follow FIFO.

    • Arrays store elements in contiguous memory locations, allowing for constant time access to elements using indices.

    • Linked lists use nodes with pointers to the next node, allowing for dynamic memory allocation and insertion/deletion at any position.

    • Stacks follow Last In First Out (LIFO) principle...

  • Answered by AI
Round 4 - HR 

(2 Questions)

  • Q1. Tell me about your self
  • Ans. 

    I am a data science enthusiast with a strong background in statistics and machine learning.

    • Completed coursework in data analysis, statistical modeling, and predictive analytics

    • Proficient in programming languages such as Python, R, and SQL

    • Experience with data visualization tools like Tableau and Power BI

    • Worked on projects involving regression analysis, clustering, and classification algorithms

  • Answered by AI
  • Q2. Why you want to join this role
  • Ans. 

    I am passionate about using data to solve complex problems and make informed decisions.

    • I have a strong background in statistics, mathematics, and programming, which are essential skills for a data science role.

    • I am excited about the opportunity to work with real-world data and apply machine learning algorithms to extract valuable insights.

    • I am eager to learn from experienced data scientists and contribute to innovative

  • 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 Naukri.com and was interviewed before Oct 2023. There were 2 interview rounds.

Round 1 - Coding Test 

Python coding and sql coding

Round 2 - Technical 

(2 Questions)

  • Q1. List all the string which start with 'a'
  • Ans. 

    List of strings starting with 'a'

    • Use a loop to iterate through each string

    • Check if each string starts with 'a'

    • Add the string to the list if it starts with 'a'

  • Answered by AI
  • Q2. Find out max value from the given table
  • Ans. 

    Use SQL query to find max value from a table

    • Use SQL query SELECT MAX(column_name) FROM table_name;

    • For example, SELECT MAX(salary) FROM employees;

    • Ensure proper column name and table name are used in the query

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - great experience

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Campus Placement and was interviewed in Mar 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Verbal reasoning is a type of aptitude test that assesses your ability to understand,analyze,and interpret written information.

Round 2 - communication round 

(5 Questions)

  • Q1. TELL ME ABOUT YOURSELF
  • Ans. 

    I am a data science enthusiast with a strong background in statistics and machine learning.

    • Completed coursework in data analysis, statistical modeling, and predictive analytics

    • Proficient in programming languages such as Python, R, and SQL

    • Experience with data visualization tools like Tableau and Power BI

    • Completed projects involving regression analysis, clustering, and classification algorithms

  • Answered by AI
  • Q2. TELL ME ABOUT PROJECT
  • Ans. 

    Developed a machine learning model to predict customer churn for a telecom company.

    • Used Python and scikit-learn for data preprocessing and model building

    • Performed feature engineering to create new variables for the model

    • Evaluated model performance using metrics like accuracy, precision, and recall

  • Answered by AI
  • Q3. About skills and how did u learn them
  • Q4. Why do u want to work with us
  • Ans. 

    I am passionate about data science and believe in the impact it can have on driving insights and decision-making.

    • I am excited about the opportunity to work with a team of experienced data scientists and learn from their expertise.

    • I am impressed by the innovative projects and cutting-edge technologies that your company is involved in.

    • I am eager to apply my skills and knowledge in data science to real-world problems and

  • Answered by AI
  • Q5. How do you stay clam when talking to difficult people
  • Ans. 

    I remain calm by actively listening, staying patient, and focusing on finding common ground.

    • Practice active listening to understand their perspective

    • Stay patient and avoid reacting emotionally

    • Focus on finding common ground or a solution to the issue

    • Use positive body language and tone of voice to convey understanding and empathy

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Nov 2022. There were 3 interview rounds.

Round 1 - Technical 

(4 Questions)

  • Q1. Asked about scenario-based Small case study questions
  • Q2. Explain statistical concepts like Hypothesis testing, and type 1 and type 2 errors.
  • Ans. 

    Hypothesis testing is a statistical method to test a claim about a population parameter. Type 1 error is rejecting a true null hypothesis, and type 2 error is failing to reject a false null hypothesis.

    • Hypothesis testing involves formulating a null hypothesis and an alternative hypothesis.

    • Type 1 error occurs when we reject a null hypothesis that is actually true.

    • Type 2 error occurs when we fail to reject a null hypothes...

  • Answered by AI
  • Q3. Coding questions about Python and SQL
  • Q4. Questions about Machine learning algorithms, AUC ROC, Classification metrics
Round 2 - Technical 

(3 Questions)

  • Q1. Explain about projects working on.
  • Q2. About a small scenario-based case study, how will you perform
  • Q3. How will you handle angry clients
Round 3 - HR 

(2 Questions)

  • Q1. Situation-based questions, small management scenario, what you will do
  • Q2. More questions about you? what you like and how the organization is good for you

Interview Preparation Tips

Topics to prepare for MathCo Associate Data Scientist interview:
  • Statistics
  • Python
  • Pandas
  • SQL
  • Machine Learning
Interview preparation tips for other job seekers - Be confident, and clear your basics. Go through some real-world end-to-end projects. To get referral, search company on LinkedIn there will be many people who can refer you.
Interview experience
4
Good
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 - HR 

(1 Question)

  • Q1. Resume Screening.....
Round 3 - Technical 

(1 Question)

  • Q1. Project explanation from the resume, NLP, Python, Supervised/Unsupervised/Boosting Algorithms
Round 4 - Behavioral 

(1 Question)

  • Q1. Logical thinking.....

Interview Preparation Tips

Interview preparation tips for other job seekers - Keep a deep understanding of your projects. Do Research about the company. Be clear with python basics concepts, libraries and most asked coding questions.

Fractal Analytics Interview FAQs

How many rounds are there in Fractal Analytics Senior Data Scientist interview?
Fractal Analytics interview process usually has 2-3 rounds. The most common rounds in the Fractal Analytics interview process are Technical, Coding Test and One-on-one Round.
How to prepare for Fractal Analytics 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 Fractal Analytics. The most common topics and skills that interviewers at Fractal Analytics expect are Machine Learning, Python, Artificial Intelligence, Deep Learning and Consulting.
What are the top questions asked in Fractal Analytics Senior Data Scientist interview?

Some of the top questions asked at the Fractal Analytics Senior Data Scientist interview -

  1. What is overfitting and underfitti...read more
  2. What is K-fold ...read more
  3. The second round was more of like techno-managerial round where the panel asked...read more

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Fractal Analytics Senior Data Scientist Interview Process

based on 3 interviews in last 1 year

2 Interview rounds

  • Coding Test Round
  • Technical Round
View more

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₹17 L/yr - ₹41.5 L/yr
8% more than the average Senior Data Scientist Salary in India
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3.7/5

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