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How to Build a Career in Data Science

Choosing a right Career and to be successful in it is a big question in today’s analytics growing market, one such new vogue is data Science.

Data science involves mix of computer science, mathematics and trend spotter, their job is to decipher large data and do further analysis to drive company successfully.

The niche industry is at peak and you are thinking of building a Career in Data Science this is a right time to grab it.

The education you need?

You won’t be able to grab an opportunity until and unless you have knowledge about it in order to build a career in data science skills you need to learn.

  • Applied mathematics.
  • Programming and communication.
  • Ability to test hypotheses.
  • Languages which include Python, Hadoop, SQL, R, SPSS, and tableau.

Other than the skills mentioned above you need to have a degree in:

  • Mathematics/science/operational research/economics or in Information technology.

In order you gain more in data science field you can opt for Ph.D. in a similar field or you can attain an online course on data science in order to build more knowledge.

If you are software engineer it will be easy for you to switch on data science as most of the work involves in programming and analysis.

Where can you apply?

With an estimated of 190,000 data scientist shortage in US alone shows choosing Career in Data Science is one of the most lucrative professional rights now.

Field you can choose from are:

Data Architect:

They work closely with a user, developer and system designer by creating a blueprint for them to integrate, maintain, centralized and protect data sources.

Business intelligence analyst:

Business intelligence analyst work is to analyze the data and clearing out where the company stands, they also help in figuring out market and business trends.

Data mining engineer:

Data mining engineer also analyze the data and create an algorithm to build a further data analyzation in future.

Data scientist:

They help in translating business case into analytic agenda by understanding the data, hypotheses developing, and exploring statistical pattern to measure the impact of it in business.

They also do an analysis for future references and explain what data will affect company on future and also to find out the solution to drive a company further.

 Senior data scientist:

Senior data scientist further analysis the business future needs. Their task is to solve a highly complex business problem efficiently. Though they are much more experience their skills helps a company to drive it further with new standards.

Data engineer:

Data engineer mostly rely on software technologies and experienced to handle big amount of data efficiently. They focus more on coding, implementing request form data scientist and in cleaning up data set.

Practically when one takes data from data scientist and implementing it in code, he/she is playing a role of data engineer.

Salary:

Speaking about salary one who pursues his career in data science the lowest pay data scientist can make 60,000 $ and up, and rest you can imagine once you stabilize a Career in Data Science.

The post How to Build a Career in Data Science appeared first on IT SKills Training Blog.

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How to Build a Career in Data Science

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