How to Build a Career in Data Science 2022 – Jobs, Disciplines & Salary

In a bit to help you in your career journey, I will use this opportunity to guide you on how to build a career in data science and discuss the good opportunities in data science.

Oftentimes, I come across people who are confused about the pathway to follow to build a career that they won’t hate, regret, and also secure a good job for the future.

But in this article, I assure you something that worth your time and I promise you that you will benefit a lot from this information.

Firstly, if you have chosen to build a career in data science, then you have made a good choice and you are about to step into greatness.

What is Data Science?

Data science combines the knowledge of programming, mathematics, and statistics to extract meaningful insights from data using scientific methods, algorithms, processes, and systems to extract knowledge from data.

What do data scientists do?

The job of a data scientist is to examine and research where to fetch or extract answers to questions from related and available data.

They also source for, manage, and analyze large amounts of unstructured data and structure it into useful and presentable data, and also secure data from varied sources.

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Is Data Science a Good Career Path?

Yes! Data science is a very good career and it is profitable to venture into it. In fact, this is one of the careers that are very valuable.

Many developed countries value data science and there are so many job opportunities and places to work as a data scientist.

Where can a Data Scientist Work?

There are so many places for data scientists to work. What are the jobs of a data scientist? A data scientist can work in any of the following places:

  • Data collection companies
  • Governmental organizations
  • Technology Companies
  • Colleges and universities
  • Financial industries
  • Computer systems design
  • Research and development firms
  • Software development companies

In fact, a data scientist can work anywhere that has to do with data analysis, data evaluations, data sorting, and prediction models.

How long does it take to build a Career in Data Science?

In some countries (especially developed countries), it takes about four (4) years to build a career in data science.

Within these four years, the student can develop a new network, and gain meaningful insights and experiences in the data science field.

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Best Countries with Jobs for Data Scientist

Many developed countries value data scientists and mostly employ data scientists to handle majors data and analysis jobs.

Which Country has Better Opportunities for Data Science Jobs?

The following are the top 15 countries with good opportunities for data science jobs.

  1. United Kingdom (U.K)
  2. Switzerland
  3. United States (U.S)
  4. Australia
  5. Russia
  6. Belgium
  7. China
  8. Denmark
  9. Norway
  10. Israel
  11. Germany
  12. Italy
  13. Singapore
  14. France
  15. Japan

How can I Start a Career in Data Science?

Starting a career in data science is as simple as starting a career in any other field. Below are the steps to start a career in data science:

how to build a career in data science

1. Acquire a Bachelor’s Degree:

The first step to starting a valuable career in data science is to acquire at least a bachelor’s degree in data science or other related disciplines.

To start well and to stand out, it is advisable to acquire at least a bachelor’s degree in the following data science-related disciplines:

  • B.Sc. in Data Science
  • B.Sc. in Data Science and Analytics
  • B.Sc. in Software Development Data and Analytics
  • B.Sc. in Statistics and Data Science
  • B.Sc. in Statistics
  • B.Sc. in Data Analysis
  • B.Sc. in Machine Learning
  • B.Sc. in Computer Science
  • B.Sc. in Data Engineering
  • B.Sc. in Software Engineering
  • B.Sc. Data security

You can start online with the following colleges and universities:

  1. DeVry University
  2. Maryville University
  3. California Polytechnic State University
  4. University Of San Francisco
  5. Yale University
  6. Florida Polytechnic University

2. Choose an Area of Interest:

Another step to take to become a good data science is to choose an area of interest (which area of data science you want to focus on).

To help you make a better choice, the following are the disciplines and fields in data science that you can choose and focus on:

Data Science Disciplines:

  • Computer Science
  • Data Analysis
  • Machine Learning
  • Statistics

Fields in Data Science

  1. Applications Architect
  2. Business Intelligence Analyst
  3. Data Analyst
  4. Data Architect
  5. Data Scientist
  6. Data Security
  7. Database Administrators (DBA)
  8. Enterprise Architect
  9. Infrastructure Architect
  10. Machine Learning Engineer
  11. Machine Learning Scientist
  12. Managers
  13. Statistician
  14. Software Developers
  15. Software Engineers
  16. Systems Administrators

3. Acquire Practical Skill

The next step to take to become a good data science is to acquire enough practical skills in any of the above-listed disciplines and fields.

You start by putting the things you learn into practice. Focusing on the practical applications of things you are learning will help you discover more things.

To test how well you are doing, you can get some data science projects and try to execute them or participate in data science competitions to test your competency.

Doing this would help you get used to the practical aspect of data science and to widen your understanding of the concepts and application of data science

4. Develop and Advance your Data Analysis Skill

If you want to expand your knowledge and skill, then you must learn to develop your data science skills, advance the skill you have acquired so far and also learn from experts.

As a data scientist, some of the most important skills to develop and advance to stand out among other data scientists or analysts include:

  1. Critical Thinking skills
  2. Machine learning skills
  3. Communication skills
  4. Presentation Skills
  5. Python-Statistical Programming (R) skills
  6. Data Visualization skills
  7. Microsoft Excel skills
  8. Structured Query Language (SQL) skills
  9. Database management skills
  10. Data cleaning skills
  11. MATLAB skills
  12. Linear Algebra and Calculus skills
  13. Python skills

How do I Start a Career in Data Science with no Experience?

The following are some of the best ways to start a career in data science with no experience and to acquire data science skills:

  • Work with data scientist
  • Learn from experts
  • Get guidance and mentorship
  • Learn to communicate
  • Use online and offline learning resources
  • Join peer groups
  • Learn to network
  • Join a data science learning team
  • Take extra online classes and courses on data science.

Final Note: The Scope of data science is very wide and there are many job opportunities for data scientists in developed countries with very huge salaries.

Generally, data scientists have many employment opportunities in almost all sectors of the economy of all countries, and students that are taking up the course stand better chances of getting good jobs.

With this useful information, I believe you have known how to build a career in data science. Please do well to share your thoughts with us via the comment section.

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