Sagility Senior Data Analyst Interview Questions and Answers

Technical discussion and previous experience

Q1. Salary negotiation. Previous experience
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Q1. Walk through your project?
Ans. 
Developed a predictive model to forecast sales based on historical data
• Collected and cleaned historical sales data

• Performed exploratory data analysis to identify trends and patterns

• Built and trained a machine learning model using regression techniques

• Evaluated model performance using metrics like RMSE and MAE
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Q2. Behavioral questions?
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Q1. Questions based on Advanced Excel like Vlookup, Index match, sumifs, pivot tables
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Q2. Behavioral questions
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Q1. Salary negotiation
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Power BI report for shoe case analysis.

Q1. Basic introduction about previous projects and skillsets.
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Q2. Related to Power BI, SQL
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SAS basic Programming questions

Q1. What questions can arise based on the projects mentioned in your resume?
Ans. 
Questions can arise about data sources, methodologies, insights gained, and impact of projects mentioned in resume.
• Data sources used in the projects

• Methodologies employed for data analysis

• Insights gained from the analysis

• Impact of the projects on decision-making or outcomes
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The first round consisted of a general assessment that included tests on artificial intelligence, machine learning, data science, English, and aptitude, followed by a face-to-face interview.

Be well prepared with Excel especially

Q1. How do you handle critical work situation?
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Q2. Team work, collaboration, managerial involvement
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Q1. How do you handle co-worker's task when given to you?
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Q2. Inform the manager and have a clear communication with the co worker on the progress and perquisites.
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Q1. Introduce yourself,why should we hire u
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Basic questions on SQL, Python

Q1. Tell me about yourself ?
Ans. 
I am a data analyst with experience in analyzing and interpreting complex data sets to drive business insights.
• Experienced in using statistical analysis tools such as Python, R, and SQL

• Proficient in data visualization techniques using tools like Tableau and Power BI

• Skilled in data cleaning, data mining, and data manipulation

• Strong problem-solving and critical thinking skills

• Effective communication and presentation skil...read more
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Q2. Education qualification?
Ans. 
Bachelor's degree in a relevant field is typically required for a Data Analyst role.
• A Bachelor's degree in fields such as mathematics, statistics, computer science, or economics is commonly preferred.

• Some employers may also consider candidates with equivalent work experience or certifications.

• Advanced degrees like Master's or Ph.D. can provide a competitive edge.

• Continuing education and staying updated with the latest
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