Data Science vs. Cybersecurity: Which Career Path is Better?
Thinking about jumping into tech but can’t decide between data science and cyber-security? You’re not alone—both fields are booming, but they’ve got totally different vibes. And you’ve got TikTok influencers saying that you can get six-figure jobs in both, but what is the reality? In this blog, we’ll break down what each career is all about, the skills you’ll need, and help you figure out which path might be your perfect match.
Data Science vs. Cybersecurity: Key Skills Required
Before we look at the job opportunities it’s important to know what skills are needed for each path and see which one you’re better qualified for. This will help you see where your strengths align and which career you may be better qualified for.
Data Science vs. Cybersecurity: Similarities and Differences in Required Skills
| Skill | Data Science | Cybersecurity | Similarity |
|---|---|---|---|
| Statistics | Essential for analyzing data, running experiments, and making data-driven decisions (learn more). | Not a primary focus but useful in analyzing security patterns. | Partial overlap in analysis |
| Programming Languages | Python, R, SQL (tutorial) | Python, C++, Java, Bash | Python is used in both |
| Data Analysis & Visualization | Core skill for insights and reporting (practice questions) | Not typically required, but useful in forensic investigations | Basic data handling in both. |
| Machine Learning | Focused on building predictive models and automation | Not commonly used but relevant for advanced security threat detection | Some overlap in advanced automation |
| Networking & System Administration | Not a focus for Data Science professionals | Essential for understanding and securing IT systems | Unique to Cybersecurity |
| Ethical Hacking / Penetration Testing | Not relevant for Data Science | Core skill for identifying vulnerabilities | Exclusive to Cybersecurity |
Data Science vs. Cybersecurity: Career Opportunities
Both of these fields have plenty of job opportunities in the market, but the roles and industries differ in these two paths. Let's dive into the career opportunities for both and how you can start your job search.
If you feel like you are ready to apply for data science roles, check out these data science job boards to apply for entry-level positions.
Data Science Career Opportunities
Data science is booming everywhere, be it tech, retail, healthcare, or finance. There are hundreds of opportunities. Some of the roles you might find as a data scientist are:
- ML Engineer: This role includes building and applying ML models for predictive analysis and automation.
- Data Scientist: Analyzing massive complex data to help companies make smarter decisions.
- Data Analyst: Interpret data and provide solutions through reports and visualizations.
- BI Analyst: Using complex data to help business strategies.
Starting a career as a Data Scientist is a way to prepare you for later career roles like a CTO. Most of the techniques used to deliver insights when you are a Data Scientist are what will make you more fluent with emerging technologies such as Gen AI, and that is important for a CTO role.
Cybersecurity Career Opportunities
This field is also in high demand since companies need to protect their systems and data from digital threats. Some roles include:
- Security Engineer: To safeguard IT infrastructure, they design and implement security solutions.
- Security Consultant: Helping companies improve their cyber security strategies.
- Cyber security Analyst: Monitoring networks for data breaches.
- Ethical Hacker: Develop and test systems to identify and fix vulnerabilities.
These roles are in high demand in sectors such as government, fin tech, healthcare etc.
Cybersecurity analysts can grow into roles like CIO, CTO, or high-paying consulting gigs by mastering the protection of a company’s most valuable asset, which is data. Cybersecurity skills are in high demand for consulting, where companies seek experts to guide them in safeguarding their systems, leading to so many opportunities in this growing field.
Data Science vs. Cybersecurity: Salary
When considering a career switch or looking for ways to advance in your field, salary is often a key factor. If you're aiming to boost your credentials, a Master’s degree might give you an edge in the recruiting process. Check out whether a Master's in Data Science is the right step for you.
Average Data Scientist Salary
Data Scientists are in high demand and salaries can vary depending on experience, location, and industry. A beginner Data Scientists can earn an average of $77,626 annually and the experienced ones based in bigger cities or even tech hubs are paid as high as 193,145 dollars per year.
Average Cybersecurity Salary
Cybersecurity experts earn high as well. Entry-level Cybersecurity Analysts make an annual average of 68,260 dollars and senior-level analysts earn between $113,087 to 187,353 annually.
Data Science vs. Cybersecurity: Which is best?
If you are interested in either Data Science or Cybersecurity, follow your passion, and see your skill set. If you love data, algorithms, and predictive models, then Data Science is for you. Alternatively, if you have a strong interest in how to keep systems safe and secure and prevent cyber attacks, cybersecurity is likely a better option.
Regardless of what you choose you can start leveling up your skills today by joining boot camps and certifications, enrolling in a Master’s Program, and learning SQL, a key skill for Data Science.
At Data Lemur, you can find practice questions on Machine Learning, Statistics, SQL, and Python, along with interview guides for top companies which will help you land your dream job in Data Science or Cybersecurity.