Tesco Data Scientist Interview Questions and Answers

Q1. Intermediate level SQL questions using joins and case when
Ans. 
Intermediate SQL question focusing on joins and case when statements for data manipulation.
• Joins combine rows from two or more tables based on a related column. Example: SELECT * FROM table1 JOIN table2 ON table1.id = table2.id.

• CASE WHEN statements allow conditional logic in SQL queries. Example: SELECT name, CASE WHEN age < 18 THEN 'Minor' ELSE 'Adult' END AS age_group FROM users.

• INNER JOIN returns only matching ro...read more
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Q2. String manipulation advanced level question in python
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Q1. Past experience
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Case Study was related to customer propensity to buy.

Q1. Linear Regression Assumptions
Ans. 
Linear regression assumptions include linearity, independence, homoscedasticity, and normality.
• Assumption of linearity: The relationship between the independent and dependent variables is linear.

• Assumption of independence: The residuals are independent of each other.

• Assumption of homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.

• Assumption of normality: The resid...read more
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Q2. ML Algorithms and Evaluation Metrics.
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Q1. What is VIF(variance inflation factor)
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VIF is a measure of multicollinearity in regression analysis, indicating how much the variance of an estimated regression coefficient is increased due to collinearity.
• VIF values greater than 10 indicate high multicollinearity

• VIF is calculated for each predictor variable in a regression model

• VIF is calculated as 1 / (1 - R^2) where R^2 is the coefficient of determination from regressing a predictor on all other predicto...read more
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Q1. Why do you want to join?
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I am impressed by your company's innovative projects and collaborative work culture.
• I admire the company's commitment to cutting-edge technology and data-driven solutions.

• I am excited about the opportunity to work with a talented team of data scientists and researchers.

• Your company's reputation for fostering a collaborative and inclusive work environment is appealing to me.
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Q1. Bias and variance with respect to model
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Bias and variance are two types of errors that can occur in a model.
• Bias refers to the error introduced by approximating a real-world problem, leading to underfitting.

• Variance refers to the error introduced by modeling the noise in the training data, leading to overfitting.

• Balancing bias and variance is crucial for creating a model that generalizes well to unseen data.
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Q2. Hypotheses test
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Q1. Data explain about yourself
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Q2. Explain About yourself
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Q3. Explain knowledge and skills
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Knowledge and skills refer to the understanding and abilities that an individual possesses.
• Knowledge is the theoretical understanding of a subject or topic.

• Skills are the practical abilities to perform tasks or apply knowledge.

• Knowledge can be acquired through education, training, or experience.

• Skills are developed through practice and hands-on experience.

• Examples of knowledge include understanding of programming langu...read more
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Q4. Explain about qualification
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Qualification refers to the education, skills, and experience required for a particular job or role.
• Qualification includes academic degrees, certifications, and relevant work experience.

• It demonstrates the candidate's knowledge, expertise, and ability to perform the job.

• Examples of qualifications can be a Bachelor's degree in Computer Science, a certification in project management, or 5 years of experience in marketing...read more
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Q1. Knowledge about vacancy requirements
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