Data Science is an emerging technical field. It is the use of modern tools and techniques to pile up a vast amount of data to find unapparent patterns, attain significant and meaningful information out of data to help in making business decisions. So, to put it in Layman’s, Data Science is the formation of predicting models for future help using pre-existing data.
Heaps of big data are being collected, processed, analyzed, and formulated by means of Data Science via Artificial Intelligence. This field finds scope in many domains. Some major areas are:
Steps of a Data Science Job
Data Science jobs consist of five stages:
Job Roles in Data Science
Top job roles in Data Science are:
1. Data Analyst
Data Analyst is the most important role in data science. This job needs analyzing and organizing data after obtaining data from different sources and producing a database.
Skills needed for Data Analysts:
2. Operations Analysts
They implement new strategies or modify previously existing ones to solve problems or increase efficiency within a company. Mainly they are involved in Data management.
The skillset needed for Operations Analyst are:
3. Data Engineers
Data Engineers design, build, optimize and manage the company’s data infrastructure or information pool. They work in accord with Data Architectures by transforming data for queries.
The skillset required for Data Engineers are:
4. Database Administrator
They optimize and maintain the entire database. They protect the data, monitor it and make it easily accessible at the time of need.
Basic skills needed by Database Administrators are:
5. Machine Learning Engineer
Machine Learning Engineer is an experienced person who uses mathematical data to program computers to utilize real-world data.
The skillset needed by Machine Learning Engineers are:
6. Data Science
Data Scientists are the ones who determine the problem and come up with solutions. They determine where to find data and what questions should be answered. They also clean the captured data.
Skills used by a Data Scientist are:
7. Data Architect
A Data Architect maintains a company’s database by installing solutions that centralize and protect the data with the best security measures. They are also providing the best tools and systems to Data Engineers.
The skillset needed for a Data Architect is:
8. Statistician
They are using mathematical and statistical techniques to help analyze data. They create new methodologies for the Data Engineers. They devise new tools for making the collection, analysis, and interpretation of data easier.
A Statistician uses these skills
9. Business Analyst
Business Analyst collects data through various sources and compares it with competitors. They are good at Data visualization and Data Modeling tools. They generally have higher domain knowledge than the others Data Science professionals.
Skills used by business analysts are:
10. Data & Analytical Manager
Data and Analytical Manager is more of a supervisor with various data Science teams working under him. It is achieved with experience. It is not very common amongst the smaller industries, whereas in larger industries Data and Analytical Manager holds key to success.
The main skills for Data and Analytical Manager are:
Why Data Science is a fascinating field to enter?
Data Science is a field that continues to grow and requires more people. It has scope in almost every kind of industry.
Data science also works well in the freelancing world. Many hiring agencies are currently in search of Data Scientists. Entering into data science does not require you to be a master. You can easily start as a consultant and later on become a Data Scientist yourself.
Here is the average salary overview of different fields of data science:
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