Tokopedia Big Data Engineer Interview Questions and Answers

Q1. Basic Recommendation System Questions
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Q2. A B Testing Questions
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The assessment consists of a dataset for which we are required to build a machine learning model and submit the results along with code and detailed documentation

Q1. What are ensemble models
Ans. 
Ensemble models are machine learning models that combine multiple individual models to improve predictive performance.
• Ensemble models work by aggregating predictions from multiple models to make a final prediction.

• Common types of ensemble models include Random Forest, Gradient Boosting, and AdaBoost.

• Ensemble models are often more accurate and robust than individual models.

• They can reduce overfitting and increase genera...read more
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Q2. Difference between bagging and boosting
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Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
• Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

• Boosting involves training multiple models sequentially, where each subsequent model c...read more
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Q3. A lot of tree based questions
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SQL, Python, like case about window function

Q1. All about past project
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1.Basic SQL
2. Python based question
3.Data modelling
4. Spark
5. Cloud based questions

Sql,Python,Data Modeling and Project based questions

Q1. Salary discussion and cultural fit.
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Q2. Basic cultural fit.
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Q1. What’s your previous experience
Ans. 
I have 3 years of experience as a data analyst in the finance industry.
• Worked with large datasets to extract meaningful insights

• Performed data cleaning, transformation, and visualization

• Created and maintained dashboards and reports for stakeholders

• Conducted statistical analysis and built predictive models

• Collaborated with cross-functional teams to identify business opportunities
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Q2. What’s your skills for the current role
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I have strong skills in data analysis, including proficiency in statistical analysis, data visualization, and programming languages such as Python and SQL.
• Proficient in statistical analysis techniques

• Skilled in data visualization using tools like Tableau

• Strong programming skills in Python and SQL

• Experience with data cleaning and preprocessing

• Ability to interpret and communicate insights from data

• Familiarity with machin...read more
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Number sires, clock, logic, arithmetic, geometry

Code test basic, ans the basic knowledge, write code

Q1. What is python?
Ans. 
Python is a high-level programming language known for its simplicity and readability.
• Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.

• It emphasizes code readability and uses indentation to define code blocks.

• Python has a large standard library and a vibrant community of developers.

• Example: print('Hello, World!')

• Example: import pandas as pd
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Q2. What is python used for?
Ans. 
Python is a versatile programming language used for data analysis, web development, artificial intelligence, automation, and more.
• Data analysis and visualization

• Web development (Django, Flask)

• Artificial intelligence and machine learning (TensorFlow, PyTorch)

• Automation and scripting

• Scientific computing (NumPy, SciPy)
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Q3. What type of language is python?
Ans. 
Python is a high-level programming language known for its simplicity and readability.
• Python is an interpreted language, meaning it does not need to be compiled before running.

• It supports multiple programming paradigms, including object-oriented, imperative, and functional programming.

• Python has a large standard library and a thriving community, making it versatile and widely used.

• Example: Python is used for web develop...read more
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Q4. What is oops in python?
Ans. 
Object-oriented programming (OOP) is a programming paradigm based on the concept of 'objects', which can contain data and code.
• OOP allows for the organization of code into reusable components called classes.

• Classes can have attributes (variables) and methods (functions) associated with them.

• In Python, everything is an object, and classes can be defined using the 'class' keyword.

• Encapsulation, inheritance, and polymorph
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Q5. What is array in python?
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An array in Python is a data structure that stores a collection of elements of the same type.
• Arrays can store elements such as integers, floats, or strings.

• Arrays are indexed starting from 0, with elements accessed using their index.

• Example: arr = ['apple', 'banana', 'cherry']
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45 mins: AWS,Data warehouse,Python

Q1. Explain OOPS concepts
Ans. 
OOPS concepts refer to Object-Oriented Programming principles like Inheritance, Encapsulation, Polymorphism, and Abstraction.
• Inheritance: Allows a class to inherit properties and behavior from another class.

• Encapsulation: Bundling data and methods that operate on the data into a single unit.

• Polymorphism: Ability to present the same interface for different data types.

• Abstraction: Hiding the complex implementation detail
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Q2. Explain BigQuery
Ans. 
BigQuery is a fully managed, serverless data warehouse by Google Cloud for analyzing large datasets using SQL.
• Fully managed and serverless data warehouse

• Allows for analyzing large datasets using SQL

• Integrates with other Google Cloud services like Data Studio and AI Platform
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Q1. All about the past projects. Few basic data visualization concepts like what charts to use, what will be the best fit for a particular scenerio
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