Web Development vs. Data Science: Which Career to Pursue?

  • 10 mins read

Web Development vs. Data Science: Which Career to Pursue?

Web Development vs. Data Science: this is quite a fork in the road, isn’t it? Maybe you started learning web development in hopes of building a career out of making websites and web apps, and along the way, discovered you had a knack for data. But should you resist the temptation? 

Maybe you started out with data science after hearing someone tell you how well-paid data scientists are. But you can’t be in it for the money, ya know (yes, some folks do data science for the pure lust they have for data). Perhaps you felt that little surge of pride whenever you got a beautiful design to work flawlessly on desktop AND mobile, and you want to recreate it for the rest of your life.

So you are at a crossroads and trying to decide which career path to take. Career statistics websites can only give you so much info. Today, we’re going to take a deep dive into both fields and figure out how they tick. What’s the difference, the pros and cons of each, and which one is really right for you? Let’s talk about it a bit.

Let’s introduce the two first

Before delving into the comparison between web development and data science, it is essential to understand the fundamental concepts of each field. Web development refers to the process of building, maintaining, and optimizing websites and web applications. This typically involves creating visually appealing designs, writing code, and implementing features that enhance interactivity and user-friendliness.

On the other hand, data science involves the collection, analysis, and interpretation of complex data sets. The primary goal is to extract valuable insights and make data-driven decisions. Data scientists employ various tools and techniques, such as statistical analysis, machine learning, and data visualization, to manipulate and understand data.

At first glance, web development and data science may appear to be distinct fields. However, there is an increasing overlap between the two. As websites evolve, becoming more intricate and interactive, they generate vast amounts of data requiring analysis and interpretation. This growing connection has led many web development companies to hire data scientists to help them make sense of the data and leverage it to improve user experiences and drive business decisions.

Web Development vs. Data Science: Pros and Cons

So before you lock down on a final decision, why not actually consider their pros and cons first:

Pros of Web Development

  • High demand: With more and more businesses going online, the demand for web developers is actually constantly growing, So you could say it’s a great time to get into web development.
  • Creative outlet: Web development allows you to combine your technical skills with your creativity to build beautiful, functional websites.
  • Flexibility: Many web developers work as freelancers or remote employees, which gives them the flexibility to work from anywhere.
  • Continuous learning: The field of web development is constantly evolving, so there’s always something new to learn and explore. However, this can also be a con–read on.

Cons of Web Development

  • Rapid change: The rapid pace of change in web development means that you have to keep up with new technologies and languages constantly.
  • High stress: Deadlines and client demands can make web development a stressful career.
  • Repetitive tasks: Some web development tasks, like debugging and testing, can be tedious and repetitive. (Chat GPT might be coming to the rescue for this kind of stuff, though).
  • Technical challenges: Web development requires a strong understanding of coding, which can be intimidating for some people. If you don’t like solving puzzles and problems, you won’t enjoy this aspect.

Pros of Data Science

  • Rising Popularity: The need for data scientists is rapidly growing and is projected to continue to do so in the coming years.
  • Analytical work: Data science allows you to work with complex data sets and derive insights from them, which can be intellectually stimulating.
  • High salary: Data scientists are among the highest-paid professionals in the tech industry.
  • Wide range of industries: Data scientists are needed in various industries, from healthcare to finance to marketing.

Cons of Data Science

  • Highly technical: Data science requires a strong background in mathematics, statistics, and computer science, which can be challenging for some.
  • Time-consuming: Collecting, cleaning, and analyzing large data sets can be time-consuming and tedious.
  • Rapidly evolving field: The field of data science is constantly changing, so you have to be willing to keep up with new technologies and techniques.
  • Limited creativity: While data science is intellectually stimulating, it doesn’t offer much opportunity for creative expression.

What do they actually do?

If you enjoy problem-solving and working with visual elements, web development could be the perfect career choice for you. As a web developer, you’ll work in teams, collaborating with designers and other developers to create visually appealing and user-friendly websites and applications. You’ll need to have a keen eye for design and be proficient in coding languages like HTML, CSS, and JavaScript.

On the other hand, if you have a strong interest in mathematics and statistics, data science might be a better fit for you. As a data scientist, you’ll work with large amounts of data to uncover patterns and insights that can help businesses make informed decisions. You’ll need to be skilled in programming languages like Python or R and have a solid understanding of statistical models and algorithms.

While web developers typically work in teams, data scientists often work independently and may be responsible for presenting their findings to non-technical stakeholders. Additionally, it’s important to consider the growth potential and job market demand for each career. Data scientists are highly sought after in sectors like finance, healthcare, and technology, while web developers are in demand across a range of businesses, from tech startups to healthcare organizations.

Web Development vs. Data Science: Which One Has a Better Salary?

If you’re considering a career in tech, you might be wondering which path will lead to a higher salary: web development or data science? Well, according to Glassdoor, web developers in the US are making an average of around $105,813 per year, which is not too shabby. However, data science takes the cake, with an average salary of $113,000 per year.

But before you start dreaming of all the money you’ll make, it’s important to keep in mind that these are just estimated averages. Your actual earning potential may vary based on factors like your experience, job details, location, and industry.

It’s also worth noting that while data scientists generally earn more due to the high demand for their specialized knowledge and skills, web developers may have more opportunities for professional growth in the tech industry.

Ultimately, when considering which career path to take, you should think about more than just the salary. You’ll want to consider what kind of work you enjoy, what skills you have, and what industries interest you. 

What to expect in a typical day in the life?

day in the life

We’ve all watched those “Day in the life of a web developer” or “Day in the life of a data scientist” videos on YouTube. But, you know those are mostly a load of BS, right?

Let me give you an idea of how your day as a web developer might vary depending on the company you work for.

If you’re a freelance web developer, your day might look a bit different than someone who works for a larger company. While you’ll still spend a good portion of your day writing code and working on projects, you may also need to spend time looking for new contracts and networking to grow your client base. You might also have more flexibility in your schedule, and may be able to take some time off or work odd hours to fit around other commitments.

On the other hand, if you work for a startup, you might find that your days are much longer and more intense. Startups often have limited resources and tight deadlines, which means you may need to put in extra hours to get everything done. You might find yourself sleeping under your desk or working weekends to ensure that everything is completed on time.

If you work for a larger company, your days may be more structured and predictable. You’ll likely have a set schedule and a defined list of tasks to complete each day. However, you may also have more resources at your disposal, such as a larger team or access to more advanced technologies.

Data Scientists get the same 24 hours, but it might look a little different

You might spend the morning exploring data sets, using your analytical skills to make sense of large, complex information. This might involve creating models and algorithms to identify patterns, trends, and relationships in the data. You could be working with structured or unstructured data, such as text or images, and developing new methods to extract meaning from the information.

Throughout the day, you collaborate with other members of your team, such as software engineers, product managers, and business leaders, to help them understand the insights you’ve uncovered. You might also spend time brainstorming new research questions, developing hypotheses, and testing new approaches to data analysis.

As the day goes on, you continue to work on your data projects, often iterating and refining your work based on feedback from your team. You might take short breaks to chat with colleagues, grab a coffee or tea, or stretch your legs.

As the end of the day approaches, you review your progress and ensure that everything is on track for project deadlines. You might also spend time documenting your work and sharing your findings with non-technical stakeholders, using visualizations and other tools to make complex data more accessible to everyone.

Web Development vs. Data Science: Which One is Growing Faster?

web dev vs. data science growth

It’s also worth considering the job market for each career. Both web development and data science are in high demand, but the demand for data scientists is growing faster. So according to the Bureau of Labor Statistics, employment of web developers is projected to grow 8% from 2021 to 2031, while employment of data scientists will grow 36% over the same period.

Web development is a well-established field, and while it may not see explosive growth, it will continue to evolve and adapt to changing technologies and user demands. The rise of new technologies such as progressive web apps (PWAs), single-page applications (SPAs), and web components will continue to shape the way web applications are built and consumed.

On the other hand, data science is a relatively new field that has seen tremendous growth in recent years and is expected to continue growing at an exponential rate. With the explosion of data in the digital age, data science is becoming increasingly important for businesses to make data-driven decisions, optimize processes, and gain insights into customer behavior.

Frequently Asked Questions: Web Development vs. Data Science

Which is better, web development or data science?

Data science comes with a statistically higher salary, so it could be better in that aspect, but web development lets you tap into your creative side a bit more. Neither one is necessarily better than the other–it really comes down to your personal interests.

Is web development easier than data science?

It can be, depending on your skill set and interests. Web development and data science require different expertise, with web development relying more on creative skills such as design and user experience, and data science relying more on analytical skills such as statistics and programming. 

Can a web developer become a data scientist?

Absolutely! There is a lot of overlap between both fields. If you’ve already worked with languages like python as a web developer, you’ll find it easy to switch to data science.