Macquarie Group Data Scientist Interview Questions and Answers

Q1. What is Bert and transformer
Ans. 
Bert and transformer are models used in natural language processing for tasks like text classification and language generation.
• Bert (Bidirectional Encoder Representations from Transformers) is a transformer-based model developed by Google for NLP tasks.

• Transformer is a deep learning model architecture that uses self-attention mechanisms to process sequential data like text.

• Both Bert and transformer have been widely use...read more
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Q2. NLP pre processing techniques
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NLP pre processing techniques involve cleaning and preparing text data for analysis.
• Tokenization: breaking text into words or sentences

• Stopword removal: removing common words that do not add meaning

• Lemmatization: reducing words to their base form

• Normalization: converting text to lowercase

• Removing special characters and punctuation
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Q1. Basic questions
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Q2. Strength weakness
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Many Mcq,s.Similar to cat exam

Ml case study . Eg loan default prediction

Q1. How to extract numbers pre decimal point from a long list of decimalnumbers with efficiency
Ans. 
Use string manipulation to efficiently extract numbers before the decimal point from a list of decimal numbers.
• Split each decimal number by the decimal point and extract the number before it

• Use regular expressions to match and extract numbers before the decimal point

• Iterate through the list and extract numbers using string manipulation functions
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Q1. ML concepts , regression, regularization etc
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Python coding question and ML question

Q1. ML questions from resume + general
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Q1. Techno managerial round
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Q1. Basic statistics
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Q1. Project related
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Q1. Work done in previous companty
Ans. 
Developed machine learning models to predict customer churn and optimize marketing campaigns.
• Built predictive models using Python and scikit-learn

• Utilized SQL to extract and manipulate data for analysis

• Collaborated with cross-functional teams to implement data-driven solutions
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