Introduction
One night, I was catching up with a friend for drinks, let's call him jon (name changed). He seemed determined to become a data scientist and was mapping his career plan accordingly..
I asked him about his awareness of what a data scientist does and sniffed that he wasn't sure. So I threw this puzzle at him:
There is 4 people A, B, C y D, each with one of these designations: a data scientist, a data engineer, a data analyst and a data architect. He also had job descriptions, that I passed it on to Jon. Had to match the description with the correct designation.
To sanction him for his mistakes, had to have a drink of alcohol for every wrong match he made. Can you guess how many shots it took that night? How many would you end up taking if you were in this situation?
I'd just say he was lucky I didn't throw this puzzle at him with the 8 designations JD had that night.
The problem
While the demand for various data science roles is increasing by the day, people in the industry have used designations and descriptions somewhat vaguely. Therefore, there is a lot of confusion about who does what in the industry.
We hope this infographic "The data science industry: who does what designed by DataCamp” help to find out the ideal job. We have provided a brief description of these roles and an infographic for you to take with you..
If you have any questions regarding designations and roles, feel free to ask through the comments below. I will be as useful as my time allows. Enjoy!
Description of various data science roles:
The data scientist
Data Scientist is most likely one of the most attractive job titles you can have these days., and with an average annual salary of $ 118,70, are among the top earners in the data science industry. The data scientist has the ability to handle raw data using the latest technologies and techniques, can perform the necessary analysis and can present the acquired knowledge to its associates in an informative way.
The data analyst
Languages like R, Python and SQL are part of the basic knowledge of the data analyst. Like the data scientist role, a broad skill set is also required for the data analyst role, combining technical and analytical knowledge with ingenuity. This profile is usually searched by companies such as HP and IBM.
The data architect
The data (are collected) everywhere and, due, more and more organizations need a data architect. Industries such as banking and consumer goods use data architects to to integrate, centralize, protect and maintain your data sources. These architects often work with the latest technologies, like spark, and they always need to be on top of the game to stay relevant.
The statistician
The statistician title is regularly overlooked or replaced by more elegant-sounding job titles. It is a pity, since the statistic, with its solid foundation in statistical theories and methodologies, can be seen as the pioneer of the data science field. Often it is he who takes the information from the data and transforms it into practical knowledge. To end, although the title may sound a bit boring compared to the others on this list, modern ones statistics are always ready to quickly hit new breakthroughs and use them to benefit your research.
The database administrator
As a database administrator, you ensure that the database is accessible to all stakeholders of the organizations, is functioning legitimately and that the necessary security measures have been implemented to keep the stored data safe. You need to master different technologies ranging from SQL and XML to a more general programming language like Java.
The business analyst
This is probably the least technical profile mentioned in the infographic. But nevertheless, the business analyst compensates for this lack of technical knowledge with a deep understanding of the various business processes that exist. Therefore, a business analyst often plays the role of an intermediary between business people and technicians. Organizations looking for business analysts are companies like Uber, Dell y Oracle.
Data and analytics manager
The data and analytics manager leads the direction of the data science team. This individual builds strong and specialized skills in various advancement arrangements (SQL, R, SAS,…) with the social skills required to deal with a group. It's hard work, but if you feel up to the challenge, be sure to check out offers from companies like Coursera, Slack. Fortunately, with an average annual salary of $ 116k, financial compensation is in line with high requirements.
Author:
Martijn Theuwissen is co-founder of DataCamp, which helps people learn data science and R from their browser and at their convenience through fun videos and interactive coding challenges.
