Table Of Content
What makes it a lucrative option?
Careers you can pursue with Data Science
Data Science is a multi-disciplinary field that combines a variety of concepts and subjects. Essentially, it’s a field in technology that branches out in to mathematics, statistical science, algorithms, machine learning and even business strategies.
What is Data Science?
Data Science professionals extract relevant information from an ocean of data. The extracted information is useful to multiple business domains.
Being one of the most sought-after fields today, data scientists are crucial to business processes as they influence decision making in most organizations. As data is mined using sophisticated techniques, it gives organizations an edge over other counterparts, paving way for a booming business. Over the years, data science has emerged as key career option and with it the demand for data scientists has increased manifold.
What makes it a lucrative option?
It’s roughly estimated that around 11.5 million jobs* will be created in Data Science by the year 2026.
In today’s date, the average package range offered to a Data Scientist in the United States (US) is about $115,000 every year*. This of course is variable based on experience and education of the data scientist.
Data Scientists are essential to multiple industries – computer engineering, finance, healthcare, business analytics and many more.
As the field rounds up as top most in all three aspects – job demand, remuneration and industry relevance, it’s a lucrative career option for many.
Careers you can pursue with Data Science
1. Data Engineer and Data Analyst
The role of a data engineer is to collect, transform and interpret information and make it available to business analysts. And the role of a data analyst is to organize data, and help stakeholders understand data to make business decisions.
2. Infrastructure Engineer
Managing cloud computing modules and servers, virtual private networks (VPNs), maintaining their security, debugging and a lot more are the essential responsibilities of an infrastructure engineer.
3. Business Intelligence Developer
This professional acts as a bridge between data and the resources who seek data. A business intelligence developer is extremely valuable and indispensable to those who need their data mined but lack the technical expertise to do so. A professional would ideally develop and manage an interface that simplifies data interpretations and makes it easy to identify data trends.
4. Data Architects and Data Scientists
One of the prime responsibilities of a data architect is to design a database framework for an organization. It means developing a framework that makes data easy, accessible and at the same time keep it highly secure. On the other hand the role of a data scientist is much more research oriented. Their job is to spend their time in building relationships in retrieved data, identifying patterns, for interpretation and modelling.
5. Machine Learning Engineers
These professionals work with Artificial Intelligence (AI) algorithms, loads of scrutinising of data, making test runs and streamline machine learning models. To make a career in this field, a professional should ideally possess, statistical and programming skills at an exceptional level.
Other career options that one can pursue are Database manager, statistician, Data Warehouse engineer, etc. among the many options available.
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Its duration is up to 10 weeks and offers a flexible schedule. With just 30 lectures, you can master this subject.
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