Top Careers in Data Science with Bright Future

28-Dec-2020

The field of Data Science is growing by leaps and bounds. Daily, new advances and breakthroughs are being made in it. It is the focus of research and development of a large number of companies and industries. It has lots of branches which are full of potential and have a large number of applications across many industries and fields. The branches include Artificial Intelligence, Deep learning, Business intelligence, Data examination, Data mining, Predictive Analytics, and many others. The demand for professionals well-versed with the field of Data Science is very high right now and will only grow with time. To tap into this demand, one should take a data science certification course. Some people make comments to the effect that the field of data science is merely a fad and the hype around it will fade away in time. But the truth is far from this.

As more and more industries experience huge changes due to the power of technology, they will generate more and more data. This can be seen as follows. Technology is leading a revolution in almost all industries which exist today. So more and more businesses and organizations are introducing sophisticated technology stacks in their operation chains. This makes it much easier for businesses and organizations to record their activities such as sales, purchases, shipments, manufactured units, etc. They can record all those activities and store them in the form of electronic data. As the volume of this data grows more and more humongous, companies will require professionals well versed with the field of Data Science to handle it and help them process it. Data is a very valuable asset in modern times and companies require data scientists to help them use it as one. In order to become such a data scientist, one should get a data science certification.

Purpose of Data Science

The purpose of data science can be stated in one line as the science of identifying, locating, and extracting patterns from data. In order to do this data scientists use a diverse range of statistical and mathematical techniques and many computer science tools to analyze and evaluate data. In this way, they glean meaningful insights from the data. From these insights, they are able to communicate the emerging trends about the company’s customers or its operations to the management and they are able to make more informed and data-driven business decisions which results in higher profits for the company.

Benefits of a Data Science Certification

Data Science Careers Which Have a High Demand

1. Data Scientist

Average Salary - $139,840

Typical job requirements – Data scientists have to locate large data sets which are suitable for analysis and processing. Next they have to clean the data. This means that they have to remove the unusable sections from the data sets and make unstructured and unwieldy data seamless and structured. After that, they have to analyze the data. The analysis includes initial data investigation and exploratory data analysis. They have to run an experienced eye over the raw data sets and select one or more potential models or algorithms to apply to the datasets. If one undergoes data science certification training, one can start a career as a data scientist easily.

2. Machine Learning Engineer

Average Salary - $114,826

Typical job requirements – Machine learning engineers are responsible for designing and building machine learning systems. They are responsible for creating programs and using algorithms which enable machines to take actions and make decisions without being explicitly directed. For eg. A machine learning engineer may be asked to create software for a self-driving car or a newsfeed which displays customized content automatically. The main challenge this job role faces is introducing the ability to learn from experience in machines without programming the knowledge into them explicitly.

3. Machine Learning Scientist

Average salary - $114,121

Typical job requirements – Machine learning scientists have the responsibility of researching, designing, and implementing one of a kind and highly scalable deep learning algorithms. They have to use these algorithms for processing complex kinds of data sets such as Spatio-temporal data related to climate and high energy physics. Usually they are hired by laboratories and other research institutions and have to work on areas related to scientific studies. They are also required to possess good communication skills as they often have to promote the research results by publishing them in scholarly publications and presenting them in leading conferences.

4. Application Architect

Average Salary: $113,757

Typical job requirements – Application architects are responsible for managing the overall architecture of a business or organization. They have to build and organize the software architecture of all the software applications used by a company. They have to ensure that the suite of software applications works well together and have to design a plan regarding how they will interact with each other. They have to ensure that all the different software applications will work in synchronization seamlessly and that they will remain efficient, reliable, and scale-ready as the needs of the organization grow.

5. Enterprise Architect

Average Salary - $110,663

Typical job requirements – An enterprise architect has to keep an eye on the business processes and make sure that they improve with time. He is the person in charge of the overall functioning of the entire business’ units. He should have very good communication skills and very strong analytical skills. He should be able to determine which legacy systems of an organization should be upgraded, which should be replaced and which should be eliminated altogether. They should also be familiar with the latest trends in the technological world so that they can easily know which software, hardware, or services need to be changed or upgraded.

6. Data Architect

Average Salary - $108,278

Typical job requirements – A data architect has to develop database solutions in order to manage company information. This includes storing company data, retrieving company data, and manipulating company data. He has to configure the databases as the needs and requirements of his company change with time. He is also responsible for maintaining and improving the structure of the data solutions which his company uses. He also has to make the decision of declaring systems as legacy and too old to be usable and help migrate company data from the legacy systems to newer, more advanced systems.

7. Business Intelligence Developer

Average Salary - $81,514

Typical job requirements – Today data is the most valuable asset a business or an organization can possess. Sales volumes, company budgeting, human resources, marketing numbers – all these and other kinds of metrics are carefully collected by companies nowadays. Business Intelligence developers employ a set of practices which enable them to extract value from all these different kinds of information. They transform this information into reports which can be used practically for taking action and data visualizations which can make it easy for the management staff to comprehend and process their company’s performance on various fronts.

8. Data Analyst -

Average Salary - $62, 453

Typical job requirements – Data analysts are in charge of how the data is collected and processed by the entire business or organization. They often make recommendations about how data should be obtained, cleaned, and analyzed in order to improve the quality and efficiency of the data a company collects. They analyze all the data in the company to identify and extract patterns from the data. On the basis of these patterns, they pinpoint and convey the emerging trends in the business processes of the company to the management staff or other relevant colleagues.

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1. The Importance of Machine Learning for Data Scientists
2. Data Scientist Salaries Around the World
3. Data Science Course Admission, Fees, Duration, Syllabus and Jobs
4. Best Way to Learn Data Science Effectively
5. Data Science: A Thriving Field in 2022 With a Promising Future

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