Siemens Relationship Executive Interview Questions and Answers

Q1. Where do you see yourself in 5 years?
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Q2. What are your strengths and weaknesses?
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Q3. Tell me about yourself.
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Q1. Details about accounting knowledge as well as the previous experience and excellence in ERP usage.
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Q1. Personal information details
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Q1. Tell me something about yourself
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Q2. What is O2C cycle ?
Ans. 
O2C cycle stands for Order to Cash cycle, which is the process of receiving and fulfilling customer orders.
• Includes order processing, inventory management, invoicing, and receiving payment

• Ensures timely delivery of products/services to customers

• Helps in tracking sales, managing cash flow, and improving customer satisfaction

• Example: Customer places an order -> Order is processed -> Product is shipped -> Invoice
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Q1. Salary expectation
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Q1. Explain O2c cycle
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Q1. Work experience background
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Q1. Why join organisation
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Q1. Tell me about your experiences
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Q1. Technical round about billing
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Q1. Salary discussion
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The aptitude test is beneficial and somewhat easy.

The coding test was both successful and somewhat challenging.

Group discussions are highly beneficial.

Q1. What is the concept of Object-Oriented Programming (OOP) in Python?
Ans. 
Object-Oriented Programming (OOP) in Python is a programming paradigm based on objects and classes to structure code effectively.
• Encapsulation: Bundling data and methods that operate on the data within one unit (class). Example: class Dog with attributes and methods.

• Inheritance: Mechanism to create a new class using properties of an existing class. Example: class Bulldog inherits from class Dog.

• Polymorphism: Ability to...read more
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Q2. What can you tell me about machine learning algorithms?
Ans. 
Machine learning algorithms enable computers to learn from data and make predictions or decisions without explicit programming.
• Supervised Learning: Algorithms learn from labeled data. Example: Linear Regression for predicting house prices.

• Unsupervised Learning: Algorithms identify patterns in unlabeled data. Example: K-Means Clustering for customer segmentation.

• Reinforcement Learning: Algorithms learn by interacting wi...read more
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Q1. Can you tell me about yourself?
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Q2. What makes you a suitable candidate for this position?
Ans. 
I possess a blend of relevant skills, experience, and a strong commitment to contributing positively to your team.
• Strong analytical skills: In my previous role, I successfully analyzed market trends to improve product positioning.

• Team collaboration: I led a project team that increased efficiency by 20% through effective communication and delegation.

• Adaptability: I quickly learned new software tools that enhanced our wo...read more
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Q1. IDF discussion and understanding
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Q2. Search methodology, keyboard and classes discussion
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Invalidity patent search

Q1. Result identified during the search
Ans. 
I identified a 20% increase in customer retention after implementing a new loyalty program.
• Implemented new loyalty program

• Analyzed customer retention data before and after implementation

• Observed a 20% increase in customer retention
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Q2. Laws related to patent invalidity
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Patent invalidity laws govern the circumstances under which a patent may be deemed invalid.
• Patent invalidity can be established through prior art, lack of novelty, obviousness, or insufficient disclosure.

• Challenges to patent validity can be raised in court or through administrative proceedings.

• Invalidity can also be based on failure to meet statutory requirements or fraudulent procurement.

• Courts may invalidate a patent...read more
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Q1. Reason for change
Ans. 
Seeking new challenges and opportunities for growth.
• Looking for a new challenge to expand my skills and knowledge

• Seeking opportunities for career advancement

• Interested in working with a different team or in a different industry
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Q2. Normal questions about family
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