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Acies Global Senior Data Scientist Interview Questions and Answers
Acies Global Senior Data Scientist Interview Experiences
1 interview found
Anonymous
Selected
I applied via LinkedIn and was interviewed before May 2023. There were 2 interview rounds.
Pandas based assignment, a dummy dataset was given with three different files, there were few questions where mostly pandas was required.
(1 Question)
- Q1. Case study was given about a biscuit manufacturing company and I had to explain as a data scientist what all steps I would do.
Interview Preparation Tips
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Interview Questionnaire
1 Question
- Q1. What PCA, Decision tree and computer vision
- Ans.
PCA is a dimensionality reduction technique, decision tree is a classification algorithm, and computer vision is a field of study focused on enabling computers to interpret and understand visual information.
PCA is used to reduce the number of variables in a dataset while retaining the most important information.
Decision trees are used to classify data based on a set of rules and conditions.
Computer vision involves usin...
Skills evaluated in this interview
Interview Preparation Tips
Experience: There were 3 rounds, All related to statistics and machine learning and whatever stuffs I had mentioned in my resume. HR round was not there. The partner of the firm just briefed me a bit about the company and asked me to relax without asking any questions in the third round.
Tips: Interview will be fun if you are thorough about your resume and it will be a cakewalk to you.
General Tips: Do's :
1. Prepare for Aptitude very seriously. Puzzles are important but aptitude is must.
2. Be thorough about everything you had specified in your resume
3. Be honest while creating your resume (It helps a lot)
Don'ts :
1. Don't get broken if you are not getting selected in Day 1 or 2 or so.
2. Don't over-prepare for case interviews, they are fairly simple.
Final Tips :
Be confident about yourself. Your attitude in the interview matters a lot. And don't lie even a bit in your resume. Many got selected with a poor resume than those with huge exaggerations.
College Name: IIT Kanpur
Rohit Mishra
Selected
I applied via Company Website and was interviewed in Nov 2023. There was 1 interview round.
(1 Question)
- Q1. Can you discuss one of your project in detail and why have you chosen those specific model to start with?
I applied via Naukri.com and was interviewed in Jun 2022. There were 3 interview rounds.
(1 Question)
- Q1. Question were asked pertaining to Mathematics behind ML algorithm
(1 Question)
- Q1. Scenario based NLP Machine Learning Question
(1 Question)
- Q1. Joining and salary Negotiations
Interview Preparation Tips
You need not know all of them. But whatever you know you need to know at depth.
I applied via Company Website and was interviewed in Jan 2024. There was 1 interview round.
(1 Question)
- Q1. Share details of projects done. But interviewer had his own bias in understanding.
Interview Preparation Tips
It was good , basic projects and coding was asked
Interview Questionnaire
2 Questions
- Q1. Three skills required to be a good data scientist?
- Q2. Answer: Curious , Extremely argumentative and judgemental
(1 Question)
- Q1. Questions related to the projects that I have done and some light coding questions.
(1 Question)
- Q1. Questions related to my projects
Interview Preparation Tips
Selected
I applied via Recruitment Consulltant and was interviewed before Apr 2023. There were 2 interview rounds.
(1 Question)
- Q1. What different splitting criterion are applied in decision tree. Why random forest works better ?
- Ans.
Different splitting criteria in decision trees include Gini impurity, entropy, and misclassification error. Random forest works better due to ensemble learning and reducing overfitting.
Splitting criteria in decision trees: Gini impurity, entropy, misclassification error
Random forest works better due to ensemble learning and reducing overfitting
Random forest combines multiple decision trees to improve accuracy and gener...
(1 Question)
- Q1. Describe the process to generate embedding on your own data set
- Ans.
To generate embeddings on a data set, preprocess the data, choose a suitable embedding method, train the model, and extract the embeddings.
Preprocess the data by cleaning, tokenizing, and normalizing text data.
Choose a suitable embedding method such as Word2Vec, GloVe, or FastText.
Train the embedding model on the preprocessed data to learn the embeddings.
Extract the embeddings from the trained model to represent the da...
Skills evaluated in this interview
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Data Scientist
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Associate Data Scientist
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