Data Science: The field and the designations
The popularity of Data Science has been spreading around the world like wildfire! But, when looking at the logistics of the field, the fire is causing a blind spot for some. Of the many hundreds and thousands of aspirants who are wishing to pursue a career in data science, most of them aspire to become a data scientist. Some of you might probably be blurting out, “Obviously”. It is for these few that we dedicate this blog!
The designations, or let’s say job roles, in the field of data science are not confined to data scientists and data analysts. In this blog, we would like to list out the various job roles that are attested to this field. Through this we also aim to guide you in choosing the role that will perfectly fit your profile. On a side note, we would like you to weigh out your strengths and weaknesses in the subject so that you can make a better, well-informed choice!
So let’s get started.
1. Data Architect:
The role of a data architect revolves around big data. A data architect is responsible for designing the blueprints of data storage and data management systems by integrating several features such as data security and maintenance.
Highly skilled in database management tools such as SQL, Pig, Hive or Spark. Possess a good grip on the XML markup language.
The average salary of a Data Architect lies at 17 LPA
2. Data Engineer:
The role of a data engineer also revolves around big data. A data engineer deals with building data pipelines to transmit the latest data related to marketing, sales or revenue to data analysts and data scientists. A data engineer also deals with building entities that are required for data storage.
Highly skilled in programming languages such as Python, Java, Ruby and C++. Highly skilled in database management tools such as SQL, Pig, Hive or Spark.
The Average Salary of a Data Engineer in India can vary between 8 LPA and 16 LPA depending on one’s experience.
3. Data Scientist:
A data scientist works with data by collecting, analyzing, and extracting information from data. A data scientist should be well equipped with analytical skills as well to use the extracted information to make informed predictions and convey the same to the concerned managing officials. A data scientist should also possess machine learning skills to be able to build models to aid prediction.
Skilled in programming languages such as Python and R. Skilled in database management tools such as SQL and NoSQL. Well versed with Mathematical and statistical concepts.
The average salary of a Data Architect lies at 10 LPA
4. Data Analyst:
The role of a data analyst is similar to that of a data scientist the only difference being a data analyst only analyses and extracts information. The role of a data analyst does not involve prediction and forecasting. Also, data analyst is considered to be an entry-level position
Moderately skilled in programming languages such as R and Python. Moderately skilled in database management languages such as SQL.
The average salary of a data analyst lies between 4 LPA and 6 LPA depending on one’s experience.
5. Business Analyst:
A Business Analyst does not really need to be well versed with all the data science skills but their role involves working with data to find solutions to business problems through analysis of company’s data and make well-informed recommendations. A business analyst also acts as a mediator between the business management and the tech team.
Basic Database Management Skills in SQL. Data Analysis Skills
The average salary of a Data Architect lies at 7 LPA.
6. Business Intelligence Developer:
A BI Developer is responsible for designing and planning Business Intelligence strategies and solutions by sifting through large databases for relevant information. A BI developer should also be well versed with all the skills necessary to deploy and maintain database servers.
Skilled in Database Management tools such as SQL and NoSQL. Data Analysis and Problem Solving Skills
The Average salary of a Data Architect lies at 5 LPA.
A statistician uses statistical theories and concepts to extract useful information from data. As data is obviously in the picture, a statistician is also required to be well versed with database management tools and be able to quickly adapt to newly emerging technologies.
Skilled in database management tools such as SQL, Pig, Hive or Spark. An extensive knowledge in statistics. Skilled in Programming Languages such as r and Python.
The average salary of a Statistician lies at 6.6 LPA.
This brings us to the end of the list.
Now that you have a detailed knowledge about all the designations in the field of data sciences, you can map your own skills and interests to choose where you wish to land.
With this, we take your leave!
A Computer Science graduate by education and a content writer by profession. Currently fulfilling her zeal to write by putting pen to paper every time she comes across something that is interesting enough to let the world know