Is Data Science a Good Career? Yes. Here are 17 Reasons Why

Data scientists use cutting-edge computing technology to make sense of big data, and demand for these experts is high. If you’re a student considering first steps or looking to switch careers, you may wonder if data science is a good option.

Data science has made solutions to many problems in society and business accessible. And many have left careers in other fields to pursue it, undeterred by its technical nature.

Does this mean data science is a good career choice? We’ll answer this question and give you 17 reasons why it may be one of the best careers today. We’ll also share tips on how you can start a fulfilling data science career.

Yes, data science is one of the best careers today. It typically comes with good pay, opportunities to solve interesting problems, and better job security than other careers.

Data science careers are among the best paying today. However, Chris Holdgraf, the director of International Interactive Computing Collaboration, also contends that this profession offers an opportunity to solve meaningful problems for different communities.

This versatile discipline allows you to work in many industries, including healthcare, manufacturing, e-commerce, and financial services. As for job security, the Bureau of Labor Statistics projected a 35% growth in the employment of data scientists between 2022 and 2032.

If you’re interested in a data science career, we offer 17 reasons this move could be a good choice.

1. Good Compensation

As mentioned above, careers in data science pay well. The average base salary for a data scientist is $123,080, and the average total compensation package is $179,687.

Entry-level data scientists earn about $60,000 for their base salary. Those in management and senior data scientist positions may earn well over $400,000. For an in-depth look, check out this list on Interview Query of the highest-paying data science jobs.

2. High Demand

Securing a good job is becoming challenging. Some sources state that applicants should expect to wait at least 44 days after sending applications to receive their first offer.

However, many firms are working to build data analytics divisions within their companies, and as mentioned earlier, the demand for data scientists is projected to last for years. This should make it easier to secure a job in data science if you have the right skill set.

3. Job Security

At a time when the emergence of AI is threatening certain jobs, a career in data science is considered relatively secure, especially for those learning to use AI to improve data analysis.

Although AI is useful in data analysis, data scientists are still needed to make algorithmic decisions, break down complicated problems, and connect business problems with technical solutions.

4. Drives Real Impact in Society

The work done by data scientists is already improving the lives of many people. Data science is currently used in healthcare to predict disease outbreaks and personalize patient treatment. It’s also helping to combat healthcare fraud and accelerate the discovery of new drugs.

In the energy industry, data science is used to optimize operations and cut costs. Data from energy sources, e.g., solar panels and turbines, can be analyzed to improve the network’s reliability and help develop better storage solutions.

5. Opportunities in Different Industries

As a data scientist, you can find employment opportunities in many industries, including:

• Finance: Analyzing trading patterns in financial markets and fraud detection.
• E-commerce: Boosting sales by identifying user needs and purchase habits.
• Energy and utilities: Increasing efficiency to cut down emissions and lower costs.
• Manufacturing: Early failure detection systems to limit equipment failure.
• Transportation: Reliable route planning to minimize times and avoid hazards.

Whichever your area of interest, you’re likely to find a role for a data scientist.

6. Cuts Across Every Part of the Business

Data science can influence almost every part of a business. The insights from data analysis can be used to make better business decisions. However, analyzing data can also help when making hiring decisions, identifying new business opportunities, identifying fraud, optimizing advertising and sales strategies, planning for the future, etc.

7. Work with Top Experts in Other Fields

Data scientists often work closely with other experts, including software engineers, data analysts, machine learning engineers, and data engineers. Additionally, they must collaborate with or report to other departments and managers.

This creates opportunities to learn from and exchange ideas with other experts, which can enhance your career growth.

8. Growth Opportunities

Your data science career can begin as a junior data scientist under someone in a senior role. As your skills improve, you can rise to mid-level positions such as senior data scientist or business analyst.

With enough time and experience, you can also become a principal or lead data scientist. You may also qualify for wider-reaching roles such as chief technology officer. Learn more on Interview Query about the skills progression for a data scientist.

9. Flexible Education Options

You can take different educational routes to become a data scientist. Some universities offer data science as a minor. When looking for a job, data science skills, in addition to your major, can make you more marketable.

You can also pursue data science as a master’s degree or take data science courses online. With more employers prioritizing skills over certificates, the possibilities for learning data science are limitless.

10. Cutting-Edge Projects

Many cutting-edge sectors require data scientists, including natural language processing, advanced robotics, computer vision, artificial intelligence, and autonomous vehicles. A career in data science allows you to work on these futuristic projects and more.

To find out more about the kinds of projects data scientists work on, check out this list of data science projects on Interview Query.

11. Remote Working Opportunities

In many companies, every aspect of the data scientist role is done remotely. This is convenient because it cuts out commuting so you can focus on the important stuff and allows you to work for overseas companies that would otherwise be inaccessible.

12. Great Internship Opportunities

Many of the biggest companies in the world rely on analytics. This has created great internship opportunities for upcoming data scientists. Some companies offering internships in data science include Honeywell, TikTok, Microsoft, and GE Healthcare.

Check out this list of top data science companies on Interview Query to see the companies you could intern for.

13. Become Part of a Growing Community

The field of data science is relatively new, but this growing community is also tight-knit. Fresh data scientists can access the expertise and support of experienced seniors with different backgrounds, leading to professional and personal growth opportunities.

14. Make Groundbreaking Contributions Faster

Data science, powered by tools like big data and machine learning, has enabled faster breakthroughs. One example is how data science is speeding up drug discoveries. This means you may not have to wait for years to experience a career-defining moment.

15. Work as a Consultant

With data science skills, you can also become your own boss and set up a consultancy. Many companies need data analytics but are not ready to create an in-house analytics team or don’t need one. This creates opportunities for you to work as an external consultant.

16. Career Satisfaction

According to a Career Explorer survey, the average career happiness score for data scientists was 3.3 out of 5. This means that a good number of data scientists were happy with their salaries, found meaning in their jobs, enjoyed their work environments, etc.

17. Leverage Existing Skills and Domain Knowledge

Switching to a data science career doesn’t mean your previous skills and domain knowledge won’t be useful. If you prefer, you can take on data science roles that benefit from your domain knowledge and skills, allowing you to build your new career on top of your existing one.

Get an Undergraduate Degree in Mathematics, Computer Science, or Statistics

Undergraduate degrees in data science are still uncommon, but a degree in one of these areas or a related field will be an advantage in this career. These fields form the foundations of data science, and the knowledge will help you when learning or practicing.

Take Advantage of Online Courses

Online courses are a great way to learn data science skills and earn certificates. These courses are less expensive than a university degree. They also make a lot of sense if you already have an undergraduate degree and are just looking to upskill before applying for data science jobs.

Build a Project Portfolio

Data science projects allow you to practice your skills, learn new ones, and become familiar with the types of problems you’ll work on as a data scientist. These projects can also be added to your resume to demonstrate your skills when applying for jobs.

Build Networks with Other Data Professionals

Many companies rely on connections and referrals to recruit new talent. To take advantage of this, start building your professional network early in your data science journey. Building a network with data professionals puts you on their radar in case their companies or someone else needs a referral. Networking also gives you opportunities to learn from other professionals.

Gain Experience via Entry-Level Positions and Internships

Performing data science on the job will accelerate your learning and career. You won’t start at the top if you have no prior experience in data science. However, internships and entry-level positions often are the stepping stones that help you climb the ladder quickly.

What Are the Cons of Getting Into Data Science?

Careers in data science come with challenges, such as the need for domain knowledge to work in certain fields like healthcare, keeping up with the latest analytics tools and methods, and becoming proficient in the different technical fields in data science.

How Do You Know if You Are Fit for Data Science?

Individuals with good technical and analytical skills and a passion for coding and problem-solving excel in data science. It’s also a good option for individuals who’ve studied software engineering or worked in such a capacity.

Check out our comparison of data science and computer science careers to decide if data science is better for you.

Do You Need to Know Coding for Data Science?

Programming is an important skill for data scientists. You’ll need coding to use many data science tools. The two commonly used programming languages in data science are Python and R.

Interview Query offers a Python learning path where you can review the basics of Python and go over some coding interview questions.

The demand for data scientists is high because most companies need their problem-solving skills. This career comes with great pay and opportunities to grow and work on interesting projects. Many data scientists are enjoying their careers, and you probably will, too.

At Interview Query, our goal is to accelerate your career in data science. We have a data science learning path you can use to refresh your knowledge of the fundamentals, we provide company-specific questions asked in data science interviews. Also, you can compare the salaries for this position at various companies or view our data scientist company interview guides.

As a data scientist, you could play a key role in answering this generation’s big questions, and that would be a worthwhile career.

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