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Sigmoid Senior Data Scientist Lead Interview Questions and Answers

Updated 11 Jul 2024

Sigmoid Senior Data Scientist Lead Interview Experiences

1 interview found

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

I applied via Naukri.com and was interviewed in Jun 2024. There were 5 interview rounds.

Round 1 - Technical 

(4 Questions)

  • Q1. How does dropout help in neural networks?
  • Ans. 

    Dropout helps prevent overfitting in neural networks by randomly setting a fraction of input units to zero during training.

    • Dropout helps in preventing overfitting by reducing the interdependence between neurons

    • It acts as a regularization technique by randomly setting a fraction of input units to zero during training

    • Dropout forces the network to learn redundant representations, making it more robust and generalizable

    • It ...

  • Answered by AI
  • Q2. How does xgboost deal with nan values?
  • Ans. 

    XGBoost can handle missing values (NaN) by assigning them to a default direction during tree construction.

    • XGBoost treats NaN values as missing values and learns the best direction to go at each node to handle them

    • During tree construction, XGBoost assigns NaN values to the default direction based on the training data statistics

    • XGBoost can handle missing values in both input features and target variables

  • Answered by AI
  • Q3. What would you do if you see your model not performing well on a time series prediction specifically on peaks and troughs?
  • Q4. How would you deal with datasets having lots of categories
  • Ans. 

    Utilize feature engineering techniques like one-hot encoding or target encoding to handle datasets with many categories.

    • Use feature engineering techniques like one-hot encoding to convert categorical variables into numerical values

    • Consider using target encoding to encode categorical variables based on the target variable

    • Apply dimensionality reduction techniques like PCA or LDA to reduce the number of features

    • Use tree-b...

  • Answered by AI
Round 2 - Case Study 

Case study involved creating a churn model with an imbalanced dataset. It contained a lot of missing values in numerical features which were correlated, Also the scaling was highly skewed. Categorical data contained a lot of low frequency categories. They wanted a final model performance on a test dataset on chosen KPIs (I chose F1-score).

Round 3 - Technical 

(2 Questions)

  • Q1. Questions on the case study - assumptions made, why did you choose a particular KPI? What was the loss function? How did you deal with class imbalance, nan values , high number of categories? Did you perfo...
  • Q2. Questions related to past experience - I told him about my last project which was based on computer vision. Interviewer asked a lot of clarifying questions and inquired about the process
Round 4 - Behavioral interview 

(4 Questions)

  • Q1. Asked about previous projects and the business impact.
  • Q2. What challenges have you faced managing a team?
  • Q3. Asked about a hypothetical scenario, how would you help the customer with that
  • Q4. What would you do if someone in your team is not performing well
Round 5 - HR 

(2 Questions)

  • Q1. Salary Discussion
  • Q2. Previous employment history

Skills evaluated in this interview

Interview questions from similar companies

I applied via Campus Placement and was interviewed in Mar 2021. There were 3 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Random forest, time series analysis.

Interview Preparation Tips

Interview preparation tips for other job seekers - Concepts must be thorough.

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".

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
-

I applied via Company Website and was interviewed in Aug 2024. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Explain the RAG pipeline?
  • Ans. 

    RAG pipeline is a data processing pipeline used in data science to categorize data into Red, Amber, and Green based on certain criteria.

    • RAG stands for Red, Amber, Green which are used to categorize data based on certain criteria

    • Red category typically represents data that needs immediate attention or action

    • Amber category represents data that requires monitoring or further investigation

    • Green category represents data that...

  • Answered by AI
  • Q2. Explain Confusion metrics
  • Ans. 

    Confusion metrics are used to evaluate the performance of a classification model by comparing predicted values with actual values.

    • Confusion matrix is a table that describes the performance of a classification model.

    • It consists of four different metrics: True Positive, True Negative, False Positive, and False Negative.

    • These metrics are used to calculate other evaluation metrics like accuracy, precision, recall, and F1 s...

  • Answered by AI

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Campus Placement and was interviewed in Oct 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 

2hrs - sections include aptitude, machine learning, deep learning and two easy python coding questions

Round 3 - One-on-one 

(4 Questions)

  • Q1. Resume scrutiny with projects and internships
  • Q2. How to measure 45 mins duration using two identical wires
  • Q3. Partition a round cake into eight equal parts within three cuts
  • Q4. 10 coins puzzle (5 heads up and 5 tails up)

Interview Preparation Tips

Interview preparation tips for other job seekers - Thorough revision on deep learning and be clear on your internships such as workflow, why did you opted a specific component (such as tool, algorithm...etc).They test you on the basis of your resume explanation, so be honest don't try to fake some
Interview experience
1
Bad
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

DSA and ML, AI, Coding question

Round 2 - One-on-one 

(1 Question)

  • Q1. Case study which was easy
Round 3 - One-on-one 

(1 Question)

  • Q1. In depth questions on ML
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Mar 2024. There were 4 interview rounds.

Round 1 - Aptitude Test 

Test consisted 7 sections which lasted for more than a hour. There were questions related to coding , sql , analytical questions etc.

Round 2 - Coding Test 

1 python coding questions and 2 Sql question

Round 3 - Case Study 

2 case study question

Round 4 - HR 

(1 Question)

  • Q1. This was the final round . Technical+HR .

Interview Preparation Tips

Interview preparation tips for other job seekers - All the best. Interview process is too long , have patience. And be prepared , questions will be basic.
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
6-8 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed in Oct 2023. There were 4 interview rounds.

Round 1 - Coding Test 

Sql, python, Statistics mcq, Aptitude test. These were medium level questions.

Round 2 - Technical 

(3 Questions)

  • Q1. SQL and python, time complexity
  • Q2. Make 2 lists a=[1,2,3,4] b=[9,8,5,5,2,3,3,4,1,1,10,9,2,3,4,10,10,9,7,7,8] Write a program to remove duplicate of b and keep only those elements of b which are not present in a, and the final list should ...
  • Ans. 

    Remove duplicates from list b, keep elements not in list a, and sort in ascending order.

    • Create a set from list b to remove duplicates

    • Use list comprehension to keep elements not in list a

    • Sort the final list in ascending order

  • Answered by AI
  • Q3. SQL question Remove duplicate from a table tab1
  • Ans. 

    Use the DISTINCT keyword in SQL to remove duplicates from a table.

    • Use the SELECT DISTINCT statement to retrieve unique rows from the table.

    • Identify the columns that should be used to determine uniqueness.

    • Example: SELECT DISTINCT column1, column2 FROM tab1;

  • Answered by AI
Round 3 - Case Study 

Given 2 case studies on data science and asked different possibilities to improve the models.

How to work with imbalance dataset.
How to remove null values, what is features engineering.
What is PCA
What is the working of XGBOOST

Round 4 - Project discussion 

(1 Question)

  • Q1. What was last project, tell me in detail. There were different technical questions related to my project

Interview Preparation Tips

Interview preparation tips for other job seekers - Be confident and practice SQL, python, mainly pandas and numpy. Should have good knowledge on time complexity.


All the metrics of evaluating a model.
Linear regression, logestic regression, random forest, decission tree, adaboost, Gradient boosting, XGb in detail.

Recall, precision roc_curve. Auc, f1 score, mse,mae, r2, adjusted r2 score.

Is it possible that r2 score appears in minus

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Naukri.com and was interviewed in Dec 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Explain any ML model.
  • Ans. 

    Random Forest is an ensemble learning method that builds multiple decision trees and merges them together to get a more accurate and stable prediction.

    • Random Forest is a popular machine learning model used for classification and regression tasks.

    • It works by creating multiple decision trees during training and outputs the mode of the classes for classification or the average prediction for regression.

    • Random Forest is ro...

  • Answered by AI
  • Q2. Create Dataframe from two lists.
  • Ans. 

    Creating a DataFrame from two lists in Python.

    • Import the pandas library

    • Create two lists of data

    • Use pd.DataFrame() to create a DataFrame from the two lists

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Nielsen Data Scientist interview:
  • Python
  • pandas
  • ML

Sigmoid Interview FAQs

How many rounds are there in Sigmoid Senior Data Scientist Lead interview?
Sigmoid interview process usually has 5 rounds. The most common rounds in the Sigmoid interview process are Technical, Case Study and HR.
What are the top questions asked in Sigmoid Senior Data Scientist Lead interview?

Some of the top questions asked at the Sigmoid Senior Data Scientist Lead interview -

  1. How would you deal with datasets having lots of categor...read more
  2. How does dropout help in neural networ...read more
  3. How does xgboost deal with nan valu...read more

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Sigmoid Senior Data Scientist Lead Interview Process

based on 1 interview

Interview experience

4
  
Good
View more

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₹46 L/yr - ₹58 L/yr
65% more than the average Senior Data Scientist Lead Salary in India
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