Element14 Data Specialist Interview Questions and Answers

Q1. ABOUT YOUR SELF
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Q2. ABOUT YOUR FAMILY
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Few standard dsa questions were asked.

Q1. Explain projects
Ans. 
Projects are specific tasks or assignments that require a set of skills and resources to achieve a particular goal or outcome.
• Projects involve defining objectives and deliverables

• They require planning, execution, and monitoring

• Projects often have timelines and budgets

• Examples: Data analysis project to identify customer trends, Project to implement a new software system
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Q2. Introduce urself
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I am a data analyst with a strong background in statistics and data visualization.
• I have a Bachelor's degree in Statistics from XYZ University.

• I have 3 years of experience working as a data analyst at ABC Company.

• Proficient in using tools like Excel, SQL, and Tableau for data analysis.

• I have experience in creating reports and dashboards to present data insights to stakeholders.
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Q1. Where do you see Yourself in 5 years ? why Qualcomm ?
Ans. 
In 5 years, I see myself as a senior analyst at Qualcomm, utilizing my skills to drive innovation and contribute to the company's success.
• I am passionate about technology and Qualcomm's cutting-edge advancements in the semiconductor industry align with my career goals.

• I believe Qualcomm's global presence and diverse projects will provide me with ample opportunities for growth and development.

• I aim to become a subject m...read more
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Q1. Indepth knowledge about process
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Q1. Questions related to adaptability, flexibility
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Q1. Why are you leaving current job
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Q1. Questions about Product, work experience, projects involved, contribution to project
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Q1. One on one with global Engineering manager on team lead capabilities, conflict management, talent assesment, team development, learning, training,
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Q1. Dropout in. Deep learning
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Q1. Explain about the project
Ans. 
Developed a machine learning model to predict customer churn for a telecom company
• Used historical customer data to train the model

• Implemented various classification algorithms such as logistic regression, random forest, and XGBoost

• Evaluated model performance using metrics like accuracy, precision, recall, and F1 score
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Q2. Basic SQLQuestions
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Q1. Intermediate level SQL questions
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Q2. Intermediate level python/machine learning questions
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Q1. Basic about python
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