Is Data Science a Good Career in 2024?

It's hard to go even a day without hearing something about data, AI, algorithms, and the like. Our world is saturated with so much unsorted and overwhelming amounts of information that experts encourage us to take a break from this digital realm for our well-being. However, it can't be denied that most of this data is relevant and helpful once it is understood.

Data scientists are vital to making sure this happens. They analyze and sort data to make predictions to inform companies and virus institutions to make the best decisions. As we'll see, it's also a rewarding career path.

Before we dive into the details, check out the video by Shane Hummus below.

Why is data science a good career path?

Data science offers a wealth of opportunities, from salary growth to job options. Those with a data science background can become machine learning engineers and data engineers, database administrators, and pursue entrepreneurial and teaching endeavours.

Is a data science career worth it?

As explained in the video by Ken Jee below, data science may be seen as a 'sexy' career by the likes of the Harvard Business Review (no small feat if you ask us). Still, bells and whistles don't guarantee a profitable and worthwhile career. Salary, work-life balance, advancement opportunities, and benefits are vital when choosing your next job.

Check out the video for Ken's take on whether a data science career is worth its title.

Benefits of a Data Science Career

Flexibility

Most data science professionals work from home or in a hybrid setup, as the nature of tech work is remote, usually requiring nothing more than a laptop and an internet connection.

Career Advancement

Data scientists aren't pigeonholed into one career for the rest of their working life. Not only are data skills transferable between industries (meaning you can jump from healthcare to tech to logistics), there is plenty of room for growth.

The list of data careers is long, almost too long. We mentioned some earlier, but professions like data scientist, data engineer, analyst careers (marketing, business, systems, etc.), machine learning engineer, and data scientist come with a clear career path built in.

Fresh out of bootcamp or university, you'll most likely land yourself a role with "Junior" in the title. From there, swapping out "Junior" for "Mid-level" or "Senior" is a natural progression with time and experience. You can also move from something like a data scientist to a machine learning engineer with the proper certifications and extra training that isn't too hard to accomplish and typically comes with a salary bump.

Job security and satisfaction

Overall, those in data enjoy their work. In fact, 74% of technical professionals in North America are satisfied with their jobs. According to Glassdoor, Data Scientist is the third best job with a job satisfaction rating of 4.1/5 and over 10,000 job openings (in the US), though Canadian statistics are likely similar.

Tech careers generally come with good job security. Even during turbulent economic times, tech workers may experience minor setbacks. Still, they can quickly find new employment thanks to the high demand across all sectors. The Wall Street Journal reports that 79% of those laid off find new jobs within three months. In 2020, when many were losing their work, the tech sector's employment levels had already rebounded to pre-pandemic levels by May.

Is data science a high-paying job?

Another (rather undeniable) benefit of a data science career is those sweet salary perks. According to Glassdoor, the average total pay for a data scientist is $98,813 annually, with the highest reported income reaching $124,000. With senior data scientists, the average total pay sits at about $132,712. It's also important to remember that salaries vary greatly depending on the company and industry. For example, a Senior Data Scientist at the Government of Canada will make around $100,495 annually. In contrast, someone with the same title at Shopify can earn upwards of $160,812.

Among our own Data Science graduates, the average starting salary was $60,780, 39% higher than the average starting salary in Canada ($40,930).

From there, salary increases and title changes come fast and furious as you become more experienced and sharpen your skills.

Is data science really in demand?

Data science, like many other tech careers, is very much in demand. With big data growing in scope and relevance (ChatGPT ring any bells?), the need for those who can sort and make sense of the ever-growing database is rapidly increasing.

The Government of Canada's Job Bank predicts that there will be a need for 29,300 database analysts and data administrators over the next ten years. Currently, in Canada, there are 604 job openings for data scientists on Glassdoor, 1,583 for data analysts, and 4,216 for machine learning engineers. On LinkedIn, a search for "data scientist" brings up 1,967 results.

With data science and related careers growing in popularity, one might wonder if the market will become saturated. However, looking at the statistics, it's estimated that Canada faces a shortage of up to 19,000 professionals with data and analytical skills and 150,000 with deep analytical literacy. It's also important to keep in mind that for many companies, data science is still in its infancy. There is a growing demand for data engineers (as mentioned in the video above) to mature these systems and set these businesses on track for a digital future.

Is data science a stressful job?

With all its perks, some might think that the work of a data scientist can be stressful. While every job has drawbacks, the pros of a career in data science far outweigh the cons. If you're not careful, the hours can run long, and, though it depends on the company, certain employers may exploit this. However, given the natural flexibility of this career, many data scientists enjoy their work.

As with all tech careers, those just starting out may find themselves dealing with imposter syndrome. In a world where things change daily, it can be hard to keep up, especially when you get the impression that everyone around you is thriving. But it's important to remember that even those more experienced still face challenges and self-doubt. What differentiates the beginner from the long-time professional is the ability to adapt to new challenges and resist falling into the trap of comparison.

Check out this final video for an overview of why data science is a good career choice.

Possible data science jobs and career paths

When it comes to work, a background in data science not only sets you on a path to a solid salary but also gives you several career paths to follow. Generally, you’ll need to have some programming languages in your back pocket like Python, SQL, and JavaScript.

Data Scientist

As a data scientist, you'll work on data mining, then clean and organize said company data. You’ll be able to take large amounts of raw data and make sense of them to detect trends that will help organizations make better strategic decisions.

Machine Learning Engineer

Machine learning engineers are strong programmers, are good with statistics, and have a basis in software engineering. They build and upkeep machine learning systems and design tests to refine what they've built and monitor their functionality.

Data Engineer

Data engineers perform batch or real-time processing on stored data. They build and upkeep data pipelines that function as an ecosystem within an organization. This way, relevant data is readily available for data scientists.

Statistician

Statisticians perform statistical analysis or exploratory data analysis on smaller groups of data to extrapolate and learn more about a larger population. They then analyze this data to generate descriptive statistics and present their findings and how they predict the larger population they are studying will act.

Data Architect

Data architects ensure that the structures and algorithms put in place are built for performance within the system. They create new database systems and data science models and look for ways to improve the functionality of existing systems.

Data Analyst

True to their name, data analysts "analyze" and make sense of data and report their findings to the company at large. They usually perform A/B testing and web analytics and provide reports to the organization, communicating their findings effectively. Ready to launch your data science career? Lighthouse Labs's Data Science Program offers two different pathways so you can learn at a pace that fits your lifestyle. For those that can make learning their full-time job, the immersive Bootcamp option will have you job-ready in just twelve weeks. For those who prefer a more extended learning experience or have priorities that can't be put on hold, the Flex option follows the same industry-standard, top-notch program but is delivered over 30 weeks.