Data Scientist vs Data Engineer 🔥 Epic Battle of Data Science 01

Here's everything you need to know about the two roles - Data Scientist and Data Engineer - covering all aspects, including: work, average salaries and skills required. This is the very first episode of our new Epic Battle of Data Science series.

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Here's a comprehensive understanding of responsibilities and technical expertise of Data Scientist & Data Engineer:

🔥 Data Scientist and Data Engineer: Work they do?
👉 Data Scientist
Apply statistical analysis and ML to extract insights from complex data.
Develop advanced models (e.g., ChatGPT) for trend prediction and decision-making.
Conduct exploratory data analysis and visualisation.
Collaborate across teams to solve business problems with data.
Continuously refine models for improved performance.
Communicate findings through reports and presentations.

👉 Data Engineer
Design robust data infrastructure for collection and storage.
Build efficient data pipelines for seamless data flow.
Implement data validation and quality control measures.
Collaborate to understand data requirements and design solutions.
Optimise systems for scalability, performance, and security.
Monitor and troubleshoot data pipelines.

🔥 Data Scientist and Data Engineer: Average Salary?
👉 Data Scientist
Average annual salary of ₹11L
Ranging between ₹5L and 25L
Data Scientist role is handsomely rewarding path 💰💼
Reference: www.glassdoor.co.in/Salaries/data-scientist-salary…

👉 Data Engineer
Average annual salary of ₹8L
Ranging between ₹4L to 20L
Data Engineering field is rapidly growing & is promising 💰💻
Reference: www.glassdoor.co.in/Salaries/data-engineer-salary-…

🔥 Data Scientist and Data Engineer: Skills required?
👉 Data Scientists
Master the art of Python, SQL, Machine Learning, and Statistics (including EDA)

👉 Data Engineers
Excel in Scala, Hadoop, Spark, SQL, and AWS

Which role gives you the kick? 🔥 Comment now!!
Happy learning ❤️ S