Data Science: A Hot Job Opportunity

Every decade, has its hottest job opportunity. During the early 1980s and early 1990s, people were in a rush to apply investment and banking jobs. In the late 90s and early 2000s, with the growth of the internet, and most Tech graduate started specializing in software and web development. Today, it is very clear that Big Data, Machine learning and AI are occupying space in every domain.


These have already become key success factors that will determine whether a business will be successful or not. This can be well-summarized by this quote below:

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

– By Geoffrey Moore, an American Management Consultant and Author.


Big companies like Ali Baba, Microsoft, Google and IBM are investing a lot on data scientists and machine learning engineers. It comes as a no surprise that LinkedIn listed the Data Scientist job as one of the most promising jobs in 2018.
In this blog, I will discuss on the traits of Data scientists, what they possess, according to a research done by 365 Data Science, an educational career website, focused on data science. I will also give my insights on how you can begin to be a data scientist.

365 Data Science collected data of 1001 data scientist professionals from LinkedIn, with the sample data involving scientists working 40% in USA, 30% in the UK, 15% in India and 15% in other countries. This is because these 3 major countries are identified most as countries that have made big strides in Data Science and its profession. Here is the summary of their findings: Males generally dominate the field at 70%, this could be for many reasons which I won’t speculate on.But what I do know is that this does not automatically make men better (or worse) at the job or more (or less) likely to get hired. So my advice to the ladies who would like to venture in Data Science to see this as a golden opportunity as every employer strives to build a reputation with gender equality.

More than 50% of the sample population work with R and/or python. Data Science and machine learning obviously can be achieved by most programming languages, but R and Python are the friendliest in this field. This is because of the vast library and the ease of task required in achieving solutions in machine learning. Another interesting insight is that R and Python are on the rise at the expense of Java and C++. Also observed is that it is a career with strong academic background. 75% of the sample population has masters or PhD with 27% having PhD and 48% having Masters.

Academic Background and career
If you are sitting there without your ‘diplomas on the wall’, keep scrolling and reading, I will give you some insights on how you can learn data science and machine learning easily at home and become a big shot. For all I know is that we live in a generation which Bill Gates and Mark Zuckerberg dropped out of college and both have built big technological empires

Given Data Science is a relatively new field, the data scientists conducted in the research have heterogeneous academic profiles…20% of them studied computer science,19% studied statistics and mathematics, 19% did economics and social sciences, 13% data science and analysis,11% Natural sciences, 9% Engineering, other courses amounted to 9%. In general, 91% of the data scientists graduated from one of the courses.

Academic profiles of data scientists

Universities and colleges struggle to meet the growing job market demand for data scientists and companies hire intelligent candidates with different backgrounds. These people have been able to acquire the required kills on their own, through self-preparations or through extensive job training. So if you are fresh high school graduate and you want to become a data scientist, I would advise you to pick a course on Data Science or Machine Learning from Universities near you that offer the course.

This would give you a competitive advantage over the others in the job market.
To sum up 365 Data Science research, they found out that the industries hiring the most data scientists are Tech/IT industries at 43%, industrial firms 37%, financial firms 15% and healthcare at 5%. This shows that this is a career that is required in a variety of fields. Broken down to the respective countries according to the research can be

Countries in research
All said and done, if you are interested, you can check the following books and online courses which I have particularly found to be a great help:

  • AurélienGéron – Hands-On Machine Learning with Scikit-Learn and TensorFlow_Concepts, Tools, and Techniques to Build Intelligent Systems-O’Reilly Media (2017)
    This book helps greatly because it starts with the basics and builds you slowly from scratch to a pro by giving you small projects that help you grow your expertise.
  • Udemy course Machine Learning A-Z™: Hands-On Python & R In Data Science by the SuperDataScience team.
    Being a data scientist or a machine learner requires you to be at least conversant with some statistics and this course brushes up your statistics and tries to help you implement it in R or Python.


In conclusion, Data Science is a career that a fresh graduate with interest in data and statistics should indulge since we have seen that it’s one of the hottest job in the coming decade. So before it gets flooded, grab yourself some data science knowledge.

6 Responses to “Data Science: A Hot Job Opportunity”

  1. Hitesh mandwani says:

    Your article is awesome! How long does it take to complete this article? I have read through other blogs, but they are cumbersome and confusing. I hope you continue to have such quality articles to share with everyone! I believe there will be many people who share my views when they read this article from you!

  2. Roslia says:

    superb share! Thanks for sharing this informative and tremendous article.

  3. Priscillah says:

    I have always heard about data science. This is a wonderful post, especially for someone who has finished his/her secondary education.

  4. Bernice Kang'ethe says:

    Thank you very much indeed for sharing this important information, really helpful. Great job,Keep it up.

  5. Varshil Shah says:

    Enlightening post, but what is the difference between machine learning and data science?

    • Brian Njoroge says:

      Good question, people regard them as one and the same. They may be right to some degree. Data science is the processing and analysis of data that you generate for various insights that will serve a myriad of business purposes. Machine learning is part of data science. It draws aspects from statistics and algorithms to work on the data generated and extracted from multiple resources

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