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Cellworks Associate Scientist Interview Questions and Answers

Updated 25 Jan 2023

Cellworks Associate 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 Campus Placement and was interviewed before Jan 2022. There were 2 interview rounds.

Round 1 - Assignment 

Read and understand research paper assigned to you

Round 2 - One-on-one 

(2 Questions)

  • Q1. Basic molecular biology question
  • Q2. Cancer related basics

Interview Preparation Tips

Topics to prepare for Cellworks Associate Scientist interview:
  • molecular biology
  • Life Sciences
Interview preparation tips for other job seekers - Strong in basic life science topics like molecular biology, cancer.

Interview questions from similar companies

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.
  • Q2. Create Dataframe from two lists.

Interview Preparation Tips

Topics to prepare for Nielsen Data Scientist interview:
  • Python
  • pandas
  • ML
Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-

I applied via campus placement at National Institute of Technology (NIT), Warangal

Round 1 - Aptitude Test 

1 hour aptitude test

Round 2 - One-on-one 

(1 Question)

  • Q1. What is one hot encoding
Round 3 - HR 

(1 Question)

  • Q1. What is your long term goal
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via campus placement at Government College Of Education, Chandigarh, Chandigarh and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Aptitude test consists of 40 questions.

Round 2 - HR 

(2 Questions)

  • Q1. Introduce yourself with ur projects
  • Ans. 

    I am a data scientist with experience in developing predictive models and analyzing large datasets.

    • Developed a predictive model for customer churn prediction using machine learning algorithms

    • Analyzed sales data to identify key trends and patterns for business optimization

    • Implemented natural language processing techniques for sentiment analysis of customer reviews

  • Answered by AI
  • Q2. Problem statement of a case that needs solutions.
  • Ans. 

    Develop a predictive model to identify potential customers for a new product launch.

    • Define the target variable and features to be used in the model

    • Collect and preprocess relevant data for training the model

    • Select an appropriate machine learning algorithm and train the model

    • Evaluate the model's performance using metrics like accuracy, precision, and recall

    • Use the model to predict potential customers for the new product

  • Answered by AI
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
Less than 2 weeks
Result
No response

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

Round 1 - Technical 

(2 Questions)

  • Q1. Cross validation
  • Q2. How to handle imbalanced dataset
  • Ans. 

    Handling imbalanced datasets involves techniques like resampling, using different algorithms, and adjusting class weights.

    • Use resampling techniques like oversampling the minority class or undersampling the majority class.

    • Utilize algorithms that are robust to imbalanced datasets, such as Random Forest, XGBoost, or SVM.

    • Adjust class weights in the model to give more importance to the minority class.

    • Use techniques like SMO...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - most questions will be from your projects/work exp

Skills evaluated in this interview

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

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

Round 1 - Coding Test 

SQL, Python coding …

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

Given 6 coding qns related to java and html and also ML.

Round 2 - Technical 

(1 Question)

  • Q1. Explain abt projects and qns related to ML.
  • Ans. 

    Projects in machine learning involve developing algorithms to analyze and interpret data for various applications.

    • Developing a recommendation system for an e-commerce website

    • Predicting customer churn for a telecommunications company

    • Classifying images in a computer vision project

    • Anomaly detection in network traffic for cybersecurity

    • Natural language processing for sentiment analysis

  • Answered by AI
Round 3 - HR 

(1 Question)

  • Q1. Basic hr qns why straive?

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Referral and was interviewed in May 2024. There were 3 interview rounds.

Round 1 - Coding Test 

I was asked to write SQL queries for 3rd highest salary of the employee, some name filtering, group by tasks.
Python code to find the index of the maximum number without using numpy.

Round 2 - One-on-one 

(1 Question)

  • Q1. Explain the Project undertaken during the research and follow-up questions
Round 3 - Technical 

(1 Question)

  • Q1. Write pandas query to separate the names as first and last name from the full name. Drop the duplicate columns and also the missing values. Write output for the Python code. Write SQL query to retrieve t...
  • Ans. 

    Answering questions related to data science concepts and techniques.

    • Recall is the ratio of correctly predicted positive observations to the total actual positives. Precision is the ratio of correctly predicted positive observations to the total predicted positives.

    • To reduce variance in an ensemble model, techniques like bagging, boosting, and stacking can be used. Bagging involves training multiple models on different ...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Nielsen Data Scientist interview:
  • Python
  • Pandas
  • SQL
  • Machine Learning
Interview preparation tips for other job seekers - Have your basics strong.

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 at National Institute of Technology (NIT), Rourkela and was interviewed in Jun 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Simple Aptitude questions, Data interpretation and verbal

Round 2 - One-on-one 

(3 Questions)

  • Q1. Basic questions on Data Analytics, Projects mentioned
  • Q2. Code in SQL and python(moderate)
  • Ans. 

    The candidate is asked to code in SQL and Python at a moderate level.

    • Use SQL to query data from databases

    • Use Python to manipulate and analyze data

    • Practice writing SQL queries and Python scripts

  • Answered by AI
  • Q3. Machine Learning

Cellworks Interview FAQs

How many rounds are there in Cellworks Associate Scientist interview?
Cellworks interview process usually has 3 rounds. The most common rounds in the Cellworks interview process are Resume Shortlist, Assignment and One-on-one Round.
What are the top questions asked in Cellworks Associate Scientist interview?

Some of the top questions asked at the Cellworks Associate Scientist interview -

  1. Basic molecular biology quest...read more
  2. Cancer related bas...read more

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Cellworks Associate Scientist Interview Process

based on 1 interview

Interview experience

5
  
Excellent
View more

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