Dunnhumby Data Scientist Interview Questions and Answers

Q1. Explain Transformers how different from previous RNN, LSTM etc.
Ans. 
Transformers are a type of neural network architecture that utilizes self-attention mechanisms to process sequential data.
• Transformers use self-attention mechanisms to weigh the importance of different input elements, allowing for parallel processing of sequences.

• Unlike RNNs and LSTMs, Transformers do not rely on sequential processing, making them more efficient for long-range dependencies.

• Transformers have been shown ...read more
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Q2. What are different types of Attention?
Ans. 
Different types of Attention include self-attention, global attention, and local attention.
• Self-attention focuses on relationships within the input sequence itself.

• Global attention considers the entire input sequence when making predictions.

• Local attention only attends to a subset of the input sequence at a time.

• Examples include Transformer's self-attention mechanism, Bahdanau attention, and Luong attention.
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Q3. Difference between GPT and BERT model
Ans. 
GPT is a generative model while BERT is a transformer model for natural language processing.
• GPT is a generative model that predicts the next word in a sentence based on previous words.

• BERT is a transformer model that considers the context of a word by looking at the entire sentence.

• GPT is unidirectional, while BERT is bidirectional.

• GPT is better for text generation tasks, while BERT is better for understanding the cont
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Q1. Difference between Data scientist, ML and AI
Ans. 
Data scientists analyze data to gain insights, machine learning (ML) involves algorithms that improve automatically through experience, and artificial intelligence (AI) refers to machines mimicking human cognitive functions.
• Data scientists analyze large amounts of data to uncover patterns and insights.

• Machine learning involves developing algorithms that improve automatically through experience.

• Artificial intelligence r...read more
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Medium level of question are there in this section

Basic level of question are there in this section

Q1. Q. What is joints? Q. What is linear search? Q. What is your hobby?
Ans. 
Joints are connections between bones that allow movement and provide support to the body.
• Joints are found throughout the body, such as the knee, elbow, and shoulder.

• They are made up of bones, cartilage, ligaments, and synovial fluid.

• Joints enable various types of movements, including flexion, extension, rotation, and abduction.

• Different types of joints include hinge joints, ball-and-socket joints, and pivot joints.

• Join...read more
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Q2. What is joints and what is your hobby?
Ans. 
I'm not sure how joints relate to data science, but my hobby is playing guitar.
• Joints can refer to the connection between two bones in the body or the way two things are connected or joined together.

• Playing guitar is a hobby that helps me relax and unwind after a long day of working with data.

• While seemingly unrelated to data science, playing an instrument can actually improve cognitive function and creativity, which c
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Simple Classification problem with some MCQ questions

Q1. Drill down on basic ML techniques
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Q1. Project Discussion with mind sharpness check
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Q1. About past experience and expectations
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Machine learning MCQ questions. 2 model-building questions.

Q1. Basic statistics, concertation of any ML algo based on the project on resume or previous works,
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Q1. Interview with data science manager. Mostly focuses on projects on your resume.
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Q1. Salary related discussion and basic HR questions.
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There were 13 questions
2 was coding and other multiple choice questions
one coding question was wine quality test