BARC Scientist Interview Questions and Answers

Around 50 Data science questions in the MCQ format, it was conducted on hacker earth platform, wnough time was available to answer all of them

Q1. 1.Machine learning questions based on different models, kernal functions, decision trees.
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Q2. 2, They asked SQL queries and python outputs and basic definitions and differences
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DS and algorithm- Greedy algorithm/ dynamic programming- task scheduling problem.

Data science- classification problem- random forest (easy)

Explain coding data science notebook from coding round.
How do you find anomaly in time series? All methods.
Generic ML questions

Q1. Biggest regret in life?
Ans. 
Regret not pursuing a career in data science earlier
• Regret not taking the opportunity to learn data science in college

• Regret not exploring data science as a career option sooner

• Regret not realizing the potential of data science in solving complex problems

• Regret not joining data science communities and attending relevant conferences

• Regret not acquiring necessary skills and knowledge earlier
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Q2. Tell me any startup idea.
Ans. 
A startup idea for an AI-powered personal assistant for managing daily tasks and schedules.
• Develop an AI algorithm to understand user preferences and habits

• Integrate with various apps and devices to gather data

• Provide personalized recommendations and reminders

• Offer voice recognition and natural language processing capabilities

• Enable seamless synchronization across multiple platforms

• Implement advanced security measures
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Q1. What are your salary expectations?
Ans. 
I would expect a competitive salary that reflects my experience and expertise in the field of data science.
• I would consider factors such as my years of experience, the complexity of the role, and the industry standards.

• I would also take into account the company's size, location, and benefits package.

• I am open to discussing salary expectations based on the overall compensation package offered.

• I believe in fair compensat...read more
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Q2. What are your strengths and weaknesses?
Ans. 
My strengths include strong analytical skills, ability to work with large datasets, and effective communication. My weaknesses include perfectionism and occasional difficulty in prioritizing tasks.
• Strength: Strong analytical skills

• Strength: Ability to work with large datasets

• Strength: Effective communication

• Weakness: Perfectionism

• Weakness: Occasional difficulty in prioritizing tasks
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Q3. Share details of your previous job.
Ans. 
I worked as a Senior Data Scientist at XYZ Company.
• Led a team of data scientists in developing machine learning models for predictive analytics.

• Collaborated with cross-functional teams to identify business problems and provide data-driven solutions.

• Implemented data preprocessing techniques to clean and transform raw data into usable formats.

• Utilized statistical analysis and hypothesis testing to derive insights and mak...read more
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