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BIOCUBE MATRICS Data Scientist Interview Questions, Process, and Tips

Updated 21 May 2024

BIOCUBE MATRICS Data Scientist Interview Experiences

1 interview found

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

I applied via LinkedIn and was interviewed in Apr 2024. There was 1 interview round.

Round 1 - Technical 

(5 Questions)

  • Q1. What is Dropout & Batch Normalization?
  • Ans. 

    Dropout is a regularization technique to prevent overfitting by randomly setting some neuron outputs to zero during training. Batch Normalization is a technique to normalize the inputs of each layer to improve training speed and stability.

    • Dropout randomly sets a fraction of neuron outputs to zero during training to prevent overfitting.

    • Batch Normalization normalizes the inputs of each layer to improve training speed and...

  • Answered by AI
  • Q2. Explain YOLO architecture, difference with SSD?
  • Ans. 

    YOLO (You Only Look Once) is a real-time object detection system that processes images in a single pass, while SSD (Single Shot MultiBox Detector) is another object detection model that also aims for real-time processing but uses a different approach.

    • YOLO processes images in a single pass, making it faster than SSD which requires multiple passes.

    • SSD uses a fixed grid of boxes at different aspect ratios and scales to de...

  • Answered by AI
  • Q3. What is confusion Matrix?
  • Ans. 

    Confusion Matrix is a table that is often used to describe the performance of a classification model.

    • It is a 2x2 matrix that summarizes the predictions of a classification model.

    • It shows the number of true positives, true negatives, false positives, and false negatives.

    • It is useful for evaluating the performance of a model by calculating metrics like accuracy, precision, recall, and F1 score.

  • Answered by AI
  • Q4. What are optimizers in Deep Learning Models?
  • Ans. 

    Optimizers in Deep Learning Models are algorithms used to minimize the loss function by adjusting the weights of the neural network.

    • Optimizers help in updating the weights of the neural network during training to minimize the loss function.

    • Popular optimizers include Adam, SGD, RMSprop, and Adagrad.

    • Each optimizer has its own way of updating the weights based on gradients and learning rate.

    • Choosing the right optimizer ca...

  • Answered by AI
  • Q5. Difference between Right and Inner Join?
  • Ans. 

    Right join includes all records from the right table and matching records from the left table, while inner join includes only matching records from both tables.

    • Right join keeps all records from the right table, even if there are no matches in the left table.

    • Inner join only includes records that have matching values in both tables.

    • Example: If we have a table of employees and a table of departments, a right join would in...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for BIOCUBE MATRICS Data Scientist interview:
  • Computer Vision
  • Deep Learning
  • Python
  • Machine Learning
  • API
Interview preparation tips for other job seekers - Prepare your resume and Questions about Computer vision & Deep Learning.

Skills evaluated in this interview

Interview questions from similar companies

I was interviewed before Feb 2021.

Round 1 - HR 

(3 Questions)

  • Q1. Share details of your previous job.
  • Q2. Why are you looking for a change?
  • Q3. Tell me about yourself.
Round 2 - Assignment 

House price prediction

Round 3 - Technical 

(1 Question)

  • Q1. About data, data science and Pharma domain

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare with your coding skills and get ready for practical assignment

Interview Questionnaire 

1 Question

  • Q1. Please tell me something about yourself.What is your experience? What are your goals and ambitions?Why We should hire you? Strengths and weaknesses etc.
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
No response

I applied via Recruitment Consulltant and was interviewed in Oct 2024. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Pandas Manipulation
Round 1 - Technical 

(1 Question)

  • Q1. Statistics Probability questions K mean

Interview Preparation Tips

Interview preparation tips for other job seekers - tough Interview. Asked statistics question
Interview experience
2
Poor
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Job Portal and was interviewed in Dec 2022. There were 2 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 - Technical 

(2 Questions)

  • Q1. Explain difference between Faster-RCNN and Yolo v3.
  • Ans. 

    Faster-RCNN and Yolo v3 are both object detection algorithms, but differ in their approach and performance.

    • Faster-RCNN uses a two-stage approach, first generating region proposals and then classifying them.

    • Yolo v3 uses a single-stage approach, directly predicting bounding boxes and class probabilities.

    • Faster-RCNN is generally more accurate but slower, while Yolo v3 is faster but less accurate.

    • Faster-RCNN is better suit...

  • Answered by AI
  • Q2. How RNN handles exploding/vanishing Gradient?
  • Ans. 

    RNN uses techniques like gradient clipping, weight initialization, and LSTM/GRU cells to handle exploding/vanishing gradients.

    • Gradient clipping limits the magnitude of gradients during backpropagation.

    • Weight initialization techniques like Xavier initialization help in preventing vanishing gradients.

    • LSTM/GRU cells have gating mechanisms that allow the network to selectively remember or forget information.

    • Batch normaliza...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - 1.They will generally ask you Project related question. Read everything you have written in the resume.
2. Will ask you about any Papers which you have published or studied.

Skills evaluated in this interview

I applied via AmbitionBox and was interviewed in Mar 2022. There were 2 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 - Aptitude Test 

Data science For 1 hr

Interview Preparation Tips

Topics to prepare for TCS Data Scientist interview:
  • Data Analysis
  • Machine Learning
  • Python
  • MySQL
Interview preparation tips for other job seekers - I am doing my Engineering in Computer science 3rd year. I have completed my data science course.
Interview experience
3
Average
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I was interviewed in Oct 2024.

Round 1 - Technical 

(1 Question)

  • Q1. Project related questions from your CV
Round 2 - Technical 

(2 Questions)

  • Q1. Question on transformers
  • Q2. Comparison of transfer learning and fintuning.
  • Ans. 

    Transfer learning involves using pre-trained models on a different task, while fine-tuning involves further training a pre-trained model on a specific task.

    • Transfer learning uses knowledge gained from one task to improve learning on a different task.

    • Fine-tuning involves adjusting the parameters of a pre-trained model to better fit a specific task.

    • Transfer learning is faster and requires less data compared to training a...

  • Answered by AI

Skills evaluated in this interview

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

2 hours of coding with 2 Questions

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

I applied via Indeed and was interviewed before Sep 2023. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. NLP techniques, word stop,
  • Q2. K-nearset neighout algorithm, gaussian mixtture model

BIOCUBE MATRICS Interview FAQs

How many rounds are there in BIOCUBE MATRICS Data Scientist interview?
BIOCUBE MATRICS interview process usually has 1 rounds. The most common rounds in the BIOCUBE MATRICS interview process are Technical.
How to prepare for BIOCUBE MATRICS 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 BIOCUBE MATRICS. The most common topics and skills that interviewers at BIOCUBE MATRICS expect are Computer Vision, Data Science, Deep Learning, Machine Learning and Python.
What are the top questions asked in BIOCUBE MATRICS Data Scientist interview?

Some of the top questions asked at the BIOCUBE MATRICS Data Scientist interview -

  1. What are optimizers in Deep Learning Mode...read more
  2. What is Dropout & Batch Normalizati...read more
  3. Explain YOLO architecture, difference with S...read more

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BIOCUBE MATRICS Data Scientist Interview Process

based on 1 interview

Interview experience

5
  
Excellent
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BIOCUBE MATRICS Data Scientist Salary
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₹4.8 L/yr - ₹10 L/yr
47% less than the average Data Scientist Salary in India
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