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Data Scientist vs Data Engineer 🔥 Epic Battle of Data Science 01
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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 💰💼
👉 Data Engineer
- Average annual salary of ₹8L
- Ranging between ₹4L to 20L
- Data Engineering field is rapidly growing & is promising 💰💻
🔥 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 ❤️ Save for later.
Save a link to this and share it among peers ❤️
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 💰💼
👉 Data Engineer
- Average annual salary of ₹8L
- Ranging between ₹4L to 20L
- Data Engineering field is rapidly growing & is promising 💰💻
🔥 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 ❤️ Save for later.
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