Bazaarvoice Data Scientist Interview Questions and Answers

My CGPA is low because I focused more on gaining practical experience through internships and projects.

• I prioritized gaining practical experience over theoretical knowledge

• I took up internships and projects to gain hands-on experience

• I believe practical experience is more valuable than just academic grades

I have experience in data analysis, machine learning, and statistical modeling.

• Worked as a data analyst at XYZ company for 2 years

• Developed predictive models using machine learning algorithms

• Conducted statistical analysis on large datasets

• Completed a Master's degree in Data Science from ABC University

Low CPI may be due to various factors such as low demand, high competition, or ineffective marketing strategies.

• Low demand for the product or service

• High competition in the market

• Ineffective marketing strategies

• Lack of differentiation from competitors

• Poor product quality or customer service

• Economic downturn or recession

• Changes in consumer behavior or preferences

Low CPI may indicate inefficiencies in marketing strategies or poor product quality.

• Low CPI can be caused by ineffective targeting of ads to the right audience.

• It can also be due to poor product quality or lack of demand for the product.

• Low CPI may require a reassessment of marketing strategies and product offerings.

• Examples of low CPI include unsuccessful ad campaigns or low sales numbers.

• Improving CPI can lead to inc...read more

I have 3 years of experience in analytics, working with various tools and techniques.

• Worked with SQL, Python, and R for data analysis and visualization

• Developed predictive models using machine learning algorithms

• Collaborated with cross-functional teams to provide insights and recommendations

• Presented findings to stakeholders and executives

• Experience in A/B testing and experimentation

• Worked with large datasets and data ...read more

ML is a subset of AI that involves training models on data, while DL is a subset of ML that uses neural networks to learn from data.

• ML involves using algorithms to learn patterns from data

• DL is a type of ML that uses neural networks to learn from data

• DL requires large amounts of data and computing power

• DL is used for complex tasks such as image and speech recognition

• ML is used for a wide range of applications such as f