Explosive Demand For Data Science And AI

Data Science and Big Data Analytics, Is it just a Hype?

As said by the Harvard Business Review, “Data Scientist: The Sexiest Job of the 21st Century”.

Data science is going big and expanding in this era, so there will be an increase in data science positions such as; data scientist, business intelligence specialist, data engineer, AI engineer, data analyst, machine learning engineer, and more.

Fields in data science might be the place for job security in high-ranking professional positions.

Check out some of the highly sought-after data science careers that make it hot and exciting.

What exactly does it mean to work in the field of data science?

You will be dealing with unstructured or structured data, analyzing, extracting, identifying trends, and interpreting them for actionable insights in organizations. Still, of course, there is a lot more than just doing that. To become a data scientist or get involved in the field, you would need a foundation in maths, computer science, statistics, and a computer programming background.

The basic process for a data science project is below. Normally a data science team consists of a number of data professionals such as data analysts, data engineers, data scientists, business unit managers, and developers. To carry out the entire data science project, the team will need to collaborate and work together and align the project to a business objective. Normally data science is a team sport, not something that could be done by one person alone.

What is the importance of data science in the world?

“”— Satya Nadella, CEO of Microsoft

Image source: caixinglobal.com

As mentioned previously, it is a growing field and applied to almost all industries like healthcare, the education sector, or the business world. Its purpose is to provide organizations to make faster and better decisions based on the data that are processed and analyzed.

A 2017 PwC survey highlighted this trend, as cross-sectoral business leaders responded that by 2020, Data Science and Analytics skills would be “required of all managers” in their respective companies.

Companies use data science to recognize and understand their consumers/users; this creates a connection between sellers and their clients. Data science has a crucial role in improving and functioning any product, and building product connections, linking consumers to the right products. Lastly, data science resolves IT and resource management issues that may be too complicated for people to find solutions efficiently.

Some statistics about the demand of Data Science and Analytics around the World

APEC commissioned a research study on the skills shortage in DSA within the region under Project DARE (Data Analytics Raising Employment), co-led by the United States Department of Labor, Wiley, and the Business Higher Education Forum (BHEF).

In 2012, Gartner forecast the creation of 960,000 new DSA jobs in Asia-Pacific by 2015 due to increased investment in DSA, but warned that only one-third of these positions would be staffed as a result of skills shortages.

1. “The United States alone faces a shortage of 140,000 To 190,000 people with analytical expertise and 1.5 Million managers and analysts with the skills to understand and make decisions based on the analysis of big data.” – McKinsey Report on BIG DATA
2. “Starting salaries for data scientists have gone north of $200,000” – Bloomberg
3. “The Whitehouse Administration is investing $200 Million into big data research projects” – Mushroom Networks
4. “Data scientists are the new superheroes,” says Pascal Clement, the Head of Amadeus Travel Intelligence in Madrid
5. “Malaysia needs additional 12,000 Data Scientists” – Ministry of Education
6. “Data Scientist: The Sexiest Job of the 21st  Century – Harvard Business Review
7. “By the year 2020, it is envisioned that Malaysia will need to reach 15,000 Data Professionals”– Multimedia Development Corporation (MDeC)
8. “12,000 Big Data scientists are needed within the next five years to spur Malaysia’sdata-driven economy” – Datuk Seri Idris Jusoh, Higher Education Minister (September 2015)
9. “We have partnered with five universities in Malaysia to embed analytics into their computer science curriculum. Also, we are working with these universities to upgrade the Syllabus to produce data scientists to address future needs” – Paul Moung, Managing Director Of IBM Malaysia

Around the world, the data economy is transforming employer needs in every sector, with growing demands for not just data science and analytics professionals (i.e., data scientists, data analysts, etc.) but also analytics-enabled workers—workers who do not work solely with data but leverage data to make decisions to support their job functions.

Why should you get involved in data science?

Here are a couple of reasons:

1. There will be many job openings, and some are currently on the lookout for data science graduates and workers. Linkedin, an online service for you to build a professional network, has noted that data science has the fastest growing number of jobs, so be part of this multidisciplinary field to increase your chances of getting employed.
2. You will develop personal growth. Problem-solving skills and presentation skills of innovations and solutions are needed in data science.
3. Fields in data science have high-paying careers; for example, based on the University of Wisconsin Data Science‘s website, experienced data scientists make an average of US$100,560, experienced data analyst US$65,000-$110,000, data engineer expert US$100,000-$165,000. The start of a data career may be around US$70,000.
4. Data science will give you opportunities to work in and find different fields of interest. It is used in industries such as; medicine, finance, media, manufacturing, etc. So you do not have to worry about being stuck in one particular field.
5. You do not have to do repetitive tasks; organizations are already training machines to handle those tiresome tasks.
6. Want to part of big companies? Microsoft, Amazon, Facebook, Apple, and Google recorded to have a high-level of data employees.

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Recommends 10 High Demand Data Science and Analytics Competencies

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