KPMG India Associate Consultant Interview Questions, Process, and Tips

Q1. Explain Machine learning lifecycle and what are the deployment options?
Ans. 
Machine learning lifecycle involves data collection, model training, evaluation, and deployment. Deployment options include cloud, on-premise, and edge computing.
• Machine learning lifecycle stages: data collection, data preprocessing, model training, model evaluation, model deployment

• Deployment options: cloud (e.g. AWS, Azure), on-premise servers, edge computing devices (e.g. IoT devices)

• Deployment considerations: scala...read more
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Q2. Questions on NLP covering text preprocessing, word embeddings, sequence based models, RAG workflow.
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Q1. What are the frameworks we can use to train machine learning models?
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Frameworks for training machine learning models
• TensorFlow

• PyTorch

• Scikit-learn

• Keras

• MXNet
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Q2. What is your current and expected salary?
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I am currently earning $60,000 per year and I am looking for a salary in the range of $70,000 to $80,000 for this position.
• Current salary: $60,000 per year

• Expected salary range: $70,000 - $80,000 per year
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Pseudo code and Aptitude with English test

Q1. Some technical questions depends upon your resume
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Q2. Explain about your projects
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Two coding questions and one SQL question.

Q1. More from core Java and Java 8.
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Q2. About previous projects.
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Q1. On multi threading, core Java, Java 8.
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Q2. About previous projects.
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Q1. Managerial questions along with a small coding question.
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Q1. Grc pLATform knowledge
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Q2. Sql and plsql related
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Topic related to energy management

Q1. Just be true to your knowledge and dont try to explain something you are not aware of or you have prepared a night before, it will not sound convincing.
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Q1. Rate your excel skills
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Q2. Determine the factors necessary to forecast for expanding generation capacity(power generation )of a client upcoming 10 years.
Ans. 
Factors for forecasting expanding generation capacity of a client over 10 years
• Evaluate current energy demand trends

• Consider technological advancements in power generation

• Analyze regulatory policies and incentives for renewable energy

• Assess potential for energy storage solutions

• Forecast economic growth and industrial development

• Account for environmental concerns and sustainability goals
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Q3. Frequently used functions and other tools used in excel for data analytics.
Ans. 
Common functions and tools in Excel for data analytics
• Pivot tables for summarizing and analyzing data

• VLOOKUP and HLOOKUP for searching and retrieving data

• IF, SUMIF, and COUNTIF for conditional calculations

• Data validation for ensuring data accuracy

• Charts and graphs for visualizing data trends
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