Primus Global Technologies Senior Data Scientist Interview Questions and Answers

Q1. Basic ios Questions No DS questions
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Q2. Basic swift quesions
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Q3. In App Purchase
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Q4. Hardware Device connectivity
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SQL Test with 5 questions

Q1. Approach towards solving the SQL Queries from the test
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A systematic approach to solving SQL queries involves understanding requirements, analyzing data, and testing results.
• Understand the requirements: Clarify what data is needed and the desired output format.

• Analyze the database schema: Familiarize yourself with tables, relationships, and data types.

• Break down the query: Start with simple SELECT statements and gradually add complexity.

• Use JOINs effectively: Combine data f...read more
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Q2. Past Experiences
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Q1. Resume related Questions
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Q2. Power BI and SQL related questions. How to approach in a dashboard building process
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Q1. Communication and behavioral skills
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Q2. Introduction, Skill set, Relevant experience
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Q1. AWS - EC2, Lambda, VPC, Route53, Cognito, Cloudwatch, Kinesis, API Gateway
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Q2. ITIL - problem management, recently handled outages. SLA vs SLO. KPIs
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Q1. DevOps - SDLC explanation, Apache Tomcat, Linux Administration, Docker and Shell scripting
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Q2. Git, Python, Monitoring tools
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Q1. Salary expectations and other benefits discussion
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Q1. Salary Negotiation and salary structure explanation
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Q1. Basic Technical Interview
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Q2. Basics on Framework used
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Q3. Infrastructure related
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Q4. Process and security
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Q1. Salary expectations and negotiation
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Array and OOPS concept. Given set of questions to solve with each oops concept

Q1. Out of box thinking. Given logical puzzles and ask you to analyze and provide your understanding
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Q2. Explain the inheritance concept with car model
Ans. 
Inheritance in car model refers to the ability of a new car model to inherit features and characteristics from an existing car model.
• Inheritance allows for the creation of a new car model that shares common features with an existing car model

• The new car model can add or modify features inherited from the existing car model

• For example, a new sports car model can inherit features from a base car model such as engine, tra...read more
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Q3. Probability question with fruits and boxes
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Forecasting problem - Predict daily sku level sales

Q1. What is difference between bias and variance
Ans. 
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
• Bias is the error introduced by approximating a real-world problem, leading to underfitting.

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

• High bias can cause a model to miss relevant relationships between features and target variable.

• High variance can cause a model to ...read more
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Q2. Parametric vs non parametruc model
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Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
• Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.

• Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.

• Examples of parametric models inc...read more
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