Data Science vs. Full Stack: Which Career Path Is Better?


People with a computer science degree often find that there are many job opportunities for them, and each one offers a high paying position and lots of room for growth. But two of the most often considered are careers in data science and full-stack development.

Data science jobs pay better than full-stack development positions. Still, more than programming and being computer savvy, it also requires statistics, analysis, and other skills that are not necessary to work as a full-stack developer. Ultimately, a better career path will depend on your skills.

If you are currently figuring out which between data science and full-stack development makes better sense for you, then read on. We will be delving into how to become a data scientist or a full stack developer, as well as the pay and career opportunities each field can give you.

Important Sidenote: We interviewed 100+ data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!

What Is Data Science?

According to Burtch Works, a professional recruitment firm, data scientists are those who can help your business gather, collect, clean, transform, and analyze unstructured data. These data are not just numbers; it may be in the form of videos, social media posts, text, sensor information, or log files.

Data Scientists: Salaries

When you look at base salaries, you will find that most entry-level data science professionals earn $95,000. Naturally, as you get more experienced, you’d make more, with subject matter experts with more than eight years of experience getting about $165,000.

Managers with small teams can expect salaries are hovering around the $150,000 mark, while senior management can get a whopping $250,000.

Indeed.com writes that the average salary for data scientists in the United States amounted to around $123,500. Those with minimal experience can expect an entry-level salary of more than $104,000, while those with three to five years of experience get an average of $142,271.

However, is there a demand for data scientists? As of November 2020, there were close to 11,000 job listings for data scientists on Indeed.com.

Becoming a Data Science Professional

If you have no idea what a data scientist does, you should first check out free courses to see if this career path is for you. It can be challenging to get insights from unstructured and complicated data. Your skills should include:

  • Statistics and probabilities
  • Business analytics
  • Programming languages such as R and Python

On top of these skills, you might find it helpful to have a bachelor’s degree in computer science or statistics. More and more data science professionals are enrolling in master’s degrees to get ahead in the job.

Focus on One, or Two, Areas

Data science has many areas, including data visualization, machine learning, algorithms, data engineering, statistics, market research analysis, and management analysis.

To have a clear career path in data science, you should focus on one area and work at it. For instance, an undergraduate degree can prepare you for gathering, analyzing, and interpreting data. Your job can teach you more about machine learning, and further studies can equip you with more skills and knowledge.

More importantly, you should get certified. There are several certification tracks for data scientists, including:

Getting Hired as a Data Scientist

Getting hired is a matter of knowing where to look. Aside from job boards like Indeed.com or Monster, there are recruiters and discussion forums that you can visit to find that perfect job.

Kaggle is a good source for quality job leads and everything you need related to data science, including codes, contests, discussion boards, and networking opportunities with more than three million members. Then you have iCrunchData, which is a job board exclusive for data science professionals.

What Is a Full Stack Developer?

There are three main types of development that you can do:

  • Front end
  • Back end
  • Full-stack

Front End Development

Front end development is what coders, website designer, and front-enders do. This aspect of development focuses on what the user can see.

For example, for a web site, front end development is concerned with the web pages, how it looks, and how visitors might interact with the site.

As such, a front end developer will be expected to know:

  • Cascading Style Sheets
  • HyperText Markup Language
  • WebAssembly or JavaScript

What’s more, front end development aims for accessibility of the sites that they work on, no matter what device the user is using. Lastly, it is concerned with the performance where the website or app opens quickly and doesn’t run into any problems.

Back End Development

Back end developers take care of the necessary things for a site, application, or software. If the front end developer works on the things that the user sees and interacts with, the back end developer is focused on the behind-the-scenes stuff such as the server, infrastructure, and database.

Back end development requires you to have working knowledge in various programming languages such as Ruby, Python, or PHP.

Full Stack Development

A full-stack developer is involved in both the front and back ends. This means that a full stack developer will need to be skilled in both. 

On top of knowing HTML, JavaScript, CSS, and any of the back-end programming languages, the full-stack developer may also need to have the following skills:

  • Project management
  • Web design
  • User experience
  • Visual design

According to W3 Schools, a full stack developer would be tasked to program browsers, databases, and servers.

Job Opportunities and Salaries

How in demand are full stack developers? As of November 2020, job site Indeed.com has around 20,000 job listings for full-stack developers. Furthermore, according to the same site, the average full stack developer earns a little more than $111,000, and with bonuses, that can get up to a little less than $15,500. 

The range of salaries can also depend on your experience. Fresh graduates or those who have minimal experience typically get around $91,000. Those with three to five years of experience can expect to earn about $135,000 on average.

Becoming a Full Stack Developer: Is It Right for Everyone?

To wit, we’ve learned that a full stack developer earns around $111,000 and similarly high demand at about 20,000 job openings over at Indeed.

Compare this to the back end and front end developers:

  • Back end developer
    • Around 10,000 job openings
    • The average salary at about $128,000
  • Front end developer
    • Around 8,900 job openings 
    • The average salary at around $110,000

If you want a career in software or website development, then it makes sense that you should aim to become a full-stack developer as you get skills for both the front and back ends of the development process. 

However, if you’re looking for something to do in your free time, perhaps you’re getting back into the workforce or trying to augment your income by taking on freelancing, then you might want to focus more on either the front end or back end development. 

For example, if you’re trying to earn something extra and want to create websites for businesses, you can focus on front-end development. Or if you possess a strong background in programming or back-end related services such as .NET or NoSQL databases, you can specialize in those skills and earn more as a back end developer.

How to Become a Full Stack Developer

According to Free Code Camp, becoming a full stack developer will require you to learn the necessary skills and programming languages for both front and back-end programming. Some suggestions include:

  • Javascript
  • React
  • Vue
  • CRUD
  • NodeJS
  • Python
  • PHP
  • Ruby
  • .NET

On top of these, you should also learn about user experience and design. Then you should get it out there: build an online portfolio and find a job at any one of these sites:

  • Fullstackjob.com
  • Github Jobs
  • Stack Overflow Jobs
  • RemoteOk
  • Indeed
  • Glassdoor

Data Science vs. Full Stack: Which Career Path Is Better?

Two things are similar with both disciplines: the ability to code is an essential part of the job, and that it’s going to be difficult to excel in all areas. 

The bottom line is, you should take stock of your skills and personality traits beyond the pay and career growth. Do you have the technical skills, the analytical mind, and the ease in communicating needed to excel in data science?

Likewise, do you know the programming languages, project management, and other skills needed to work as a full-stack developer? If you don’t, you’re in luck because there are many resources that you can rely on to learn, plus you also get to know on the job.

A less technical person will do well in data science, picking up the coding skills they need along the way. For example, somebody with a mathematics background can be a great data scientist even when the programming skills are not up to par. Whereas, the same person will probably not have as much luck working as a full stack developer.

But with all things being equal, which one should you choose? The Harvard Business Review calls data scientists the sexiest job way back in 2012. But ADT Mag points out that full-stack development has overtaken data science in Indeed’s reportage on the best jobs.

Basing it on data from Indeed, if you like the money, then go for data science. However, full-stack developers have more choices when it comes to job opportunities. What’s more, they can also go for front end and back end development jobs.

Full-Stack DeveloperData Scientist
Job openings~20,000~11,000
Average salary$111,000$123,500

Author’s Recommendations: Top Data Science Resources To Consider

Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.

  • DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
  • MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
  • Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.

Conclusion

When it comes to chasing that dream of landing – and keeping – a high paying job, you can’t go wrong with either data science or full-stack development. However, a lot of which one is the best for you will depend on the skills and interest.

BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed 100+ data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.

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Daisy

Daisy is the founder of DataScienceNerd.com. Passionate for the field of Data Science, she shares her learnings and experiences in this domain, with the hope to help other Data Science enthusiasts in their path down this incredible discipline.

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