Data Science vs. Cyber Security: Which Is Best for You?

Ekene Eze · Improve this Guide

Data science and cyber security are two of the most in-demand career options in IT. Both career paths deal with analyzing complex data and come with various challenges. For beginners, a structured learning path in data science or cybersecurity can be a great starting point. However, if you already have good knowledge of both fields but find it difficult to choose the right one for your career, this guide will definitely help.

If you want to analyze large volumes of data and uncover deep insights, data science is a great fit for you. On the other hand, if you are passionate about protecting digital assets, preventing cyber threats, and ensuring information security, cyber security might be the better path for you.

Data science vs. cyber security is a common debate among tech professionals when choosing a career path, as both fields offer high salaries, strong career growth, and essential roles in modern businesses. This results in confusion among career switchers and younger graduates struggling with the choice of cyber security or data science. So, let’s compare the two based on these factors to make it easier for you to choose a career path.

In this guide, you’ll learn the job responsibilities of cyber security and data science, the required skills, and career prospects.

Differences between data science and cyber security

The following table provides a quick comparison between cyber security and data science.

	Data Science	Cyber Security
Key role	Data Scientists use computer science and statistical analysis and organizational data to analyze and solve complex business problems.	Cyber security professionals use security tools, networking fundamentals, and incorporate risk management strategies to prevent security breaches and threats.
Industries	Healthcare, technology, finance.	Software and SaaS companies, healthcare, government, etc.
Tools	TensorFlow, Pandas, Jupyter Notebooks.	Firewalls, SIEM systems, intrusion detection tools, and encryption software.
Skills	Expertise in programming, machine learning skills, statistics, data visualization, big data, natural language processing, data manipulation and data wrangling.	Knowledge of security protocols, networking fundamentals, risk management skills, incident response, penetration testing and ethical hacking.
Career paths	Data scientists, machine learning engineer, AI analysts, data engineer, data analyst.	Security analyst, cyber security engineer, information security manager, network engineer, security auditor.
Salary range	For the data science field, the salary ranges from $53,925 to $161,715 per year.	For cyber security professionals, the salary ranges from $91,123 to $136,104 per year.

What are data science and cyber security?

Data science is a multidisciplinary field focused on extracting knowledge and insights from data to solve business problems. It involves statistical methods, programming, machine learning, data analytics. and domain expertise to build models and analyze structured and unstructured data while ensuring data integrity. This field is widely applied across industries such as healthcare, tech, and finance.

Cyber security, on the other hand, focuses on protecting data and systems from cyber threats and unauthorized access. As a cybersecurity professional, you will use firewalls, intrusion detection systems, and encryption to secure systems and data while maintaining data integrity. Cyber security is crucial in software companies, SaaS platforms, healthcare, and government sectors.

Despite their differences, both data science and cyber security rely on data. For example, if you work as a data scientist in an eCommerce company, you may analyze consumer related data to recommend products and drive sales. If you are a cyber security expert in the same company, your job will be to detect and prevent fraud by analyzing transaction patterns for suspicious activity. While data science focuses on using secure data to generate insights, cybersecurity relies on large datasets to identify threats and vulnerabilities.

As data grows in volume and importance, the demand for data scientists and cyber security professionals will continue to rise. If you’re considering a career in either field, you’ll find plenty of opportunities.

Now, let’s look at the skills you need to get started in each field.

Data science vs. cyber security: Skills and tools required for each field

The data science role generally involves building predictive models based on the analyzed datasets, data cleaning, and visualizations. Cyber security, on the other hand, involves tasks like monitoring systems and performing risk assessments to protect digital assets.

Let’s go into detail and explain the different skill sets and tools that aspiring data scientists and cyber security experts must have.

Skills and tools for data science

The process of extracting data, which encompasses both structured and unstructured information, requires fundamental skills and tools that can handle the initial analysis and management challenges effectively. If you’re preparing for a data science job, you must have the technical skills to perform analyses and the interpersonal skills to communicate your findings effectively to stakeholders and team members.

Some of the key skills an interviewer looks for in a data scientist profile include:

• Expertise in programming languages: A certified data scientist must be good at different programming languages, including Python, R, SAS, and SQL. You must know the basics of these languages to sort, analyze, and manage large datasets easily.
• Machine learning skills: You should be able to sort and synthesize data while making better predictions based on your collected data. Additionally, you should be able to implement appropriate algorithms to solve complex problems.
• Statistics: The data scientist’s role involves to build models based on analysis and draw actionable insights. You must know how to use statistical analysis concepts like probability distribution and linear regression to write high-quality models and algorithms for your project.
• Data visualization: Apart from analyzing data, you must also learn skills on how to represent your work to stakeholders. So, to create charts and graphs, you must know how to use data visualization tools like Tableau and Power BI.
• Data wrangling: Expertise in techniques like cleaning and organizing complex data and pattern recognition to ease the analysis process.

If you’re applying for a data science role, you should have expertise in tools such as TensorFlow, Pandas, Jupyter Notebooks, and Tableau.

Skills and tools for cybersecurity

As a cyber security expert, you must have the technical expertise and skills to identify and respond to threats in real time.

You must excel in the following cyber security skills and tools to qualify for different career opportunities within the cyber security field:

• Networking: You must deeply understand network protocols, operating systems, security concepts, and architectures to assess vulnerabilities before attackers exploit systems.
• Risk management: Expertise in managing and mitigating cyber security risks is essential. These skills allow you to better assess the likelihood and impact of incoming known threats.
• Ethical hacking: As an ethical hacker, you’ll use the same tools and techniques as malicious hackers but with permission from the system owner. By knowing how they act and their strategies, you can improve your network security and overall security posture.
• Knowledge of security protocols: A strong understanding of the various security protocols, like encryption protocols, network security protocols, authentication protocols, etc., is a must.

In addition, you must know how to use firewalls, security information and event management (SIEM) systems, intrusion detection tools, and encryption software to qualify for different career options in cybersecurity. Managing data security is not a simple task; it requires a sharp mind and analytical thinking to beat cyber threats and respond to security breaches.

Let’s move forward to learn about the salary range for each job position to make it easier for you to compare and select based on your requirements.

Career opportunities and salary insights

As more businesses use data to make decisions, the demand for data science professionals is high among different industries. Cyber security experts are also in constant demand with the introduction of new and advanced technologies like artificial intelligence (AI) and cloud computing.

Let’s investigate the salary insights and career options available in both fields to identify your area of interest.

Data science career paths and salary insights

Planning to proceed with the data science field? If yes, the following career options are available for consideration:

• Data scientist
• Machine learning engineer
• AI specialist

Data scientist: In this role, you’ll find patterns in complex datasets, create algorithms and data models, deploy data tools, perform data analysis, and predict solutions to stakeholders based on the analysis. You can incorporate machine learning and deep learning practices to improve data quality and predict outcomes. As a data scientist, you must have a good command of your communication skills apart from technical skills and statistical modeling expertise.

The average salary of an employee pursuing a career as a senior data scientist in the United States is $123,069 per year.

Machine learning engineer: If you apply for this position, your task will be to research and build machine learning algorithms and artificial intelligence systems. Machine learning professionals are also responsible for optimizing frameworks and performing statistical analysis.

The average salary for this job role in the United States ranges around $161,715 annually.

AI specialist: Your role as an AI specialist is to develop and optimize AI systems. Hence, ensure you know the basics of AI concepts and programming. In addition, you might be responsible for AI system integration, designing AI strategies, and reinforcement learning.

According to ZipRecruiter, the average salary for an AI Specialist in the United States is $53,925 a year.

Data engineer, data analyst, and data architect are a few more job roles within data science that you can apply for.

Cyber security career paths and salary insights

If you have an interest in cybersecurity, you can choose from the following career path options:

• Security analyst
• Cyber security engineer
• Information security manager

Security analyst: As a Cyber security analyst, your main role is to identify and troubleshoot problems within security systems and protect sensitive data. Security analyst professionals monitor systems and perform compliance control testing to minimize security risks. Based on their analysis, you can also recommend reducing risk and securing systems.

According to Indeed, the average salary of a cyber security analyst in the United States is $91,123 per year.

Cyber security engineers: Cyber security engineers are the front warriors who design and configure solutions against cyber criminals. You will have to act as an ethical hacker to strategize and identify vulnerabilities before attackers exploit them.

ZipRecruiter states that the average salary of an employee pursuing a career in this position in the United States is $122,890 per year.

Information security manager: In this role, your main focus will be on developing and implementing security policies. You will also handle incident response plans, threat monitoring, and the implementation of security best practices for protecting computer systems.

According to ZipRecruiter, the average salary of a Certified Information Security Manager in the United States is $136,104 per year.

Let’s dive in and take a closer look at the work environment in both fields to help you decide which one is best for you.

Work environment differences

The work environments in data science and cyber security differ significantly, appealing to distinct personalities and work styles.

Data science typically offers a more collaborative and research-oriented atmosphere. Imagine teams of data analysts, data science professionals, and researchers brainstorming, analyzing historical data, sharing insights, and working together to find solutions for complex datasets.

Flexibility is often a key feature, both in terms of working hours and location. While deadlines exist in data science, the project-based nature often allows for a more measured pace, with timelines that can stretch over weeks or months. This allows for deep dives into data, thorough data analysis, and the development of sophisticated models.

You will be more attracted to the data science field if you enjoy intellectual exploration and the satisfaction of uncovering hidden patterns. Data science is great if you like intellectual exploration, problem solving and finding hidden patterns. It’s creative and encourages deep analysis of complex problems, so if you like structured but exploratory work, it’s a good fit.

Cyber security, on the other hand, is a high-stakes, fast-paced world. The focus is on real-time threat prevention, monitoring security infrastructure, and rapid response to security incidents.

Security professionals need to be on high alert, anticipating and countering attacks on systems. It’s intense work, with split second decisions and big consequences.

The nature of cyber security often demands irregular hours, especially during security crises. A major breach can require teams to work around the clock to contain the damage and restore systems. While this can be incredibly demanding, it can also be immensely rewarding for those who thrive in high-pressure situations and enjoy the thrill of the chase.

Whether you are planning for cyber security or data science, consider all aspects, including the work environment.

Cyber security and data science: Which path is best for you?

It’s best to keep your interests, skills, and personality in mind when selecting between cyber security and data science.

If you find yourself drawn to the world of data, enjoy the challenge of extracting meaning from raw data, and prefer coding and statistical analysis over other practices, data science might be the right path for you. Do you get excited about building predictive models, uncovering trends, and using data to solve real-world problems? If so, you’ll likely find the intellectual challenges of data science stimulating.

On the other hand, if your passion lies in protecting systems, staying one step ahead of hackers, and responding to high-stakes challenges, cybersecurity could be a more fulfilling career choice. If you love understanding cybercriminals’ psychology and preventing them from achieving their goals, this one could be your career goal.

If you still have questions about cyber security and data science, try taking online courses or doing small projects in each field to find your real interest. You can also work with datasets, experiment with different algorithms, connect with a data engineer, or explore basic cyber security concepts. This hands-on experience will give you valuable insights into your preferences.

What’s Next?

Cyber security or data science, whichever path you choose, make sure it fulfills your needs and interests. If working on numbers and models is your thing, data science is the right path for you. However, cyber security could be a better option if you are more inclined toward protecting systems and taking on challenges.

Choosing between cyber security and data science can be a difficult decision, but this guide has provided key insights to help you evaluate your interests. To further explore your options, check out cyber security and data science roadmaps to gain deeper insights into each field. You can also join online courses and get relevant certifications or connect with our experts on the Discord community to stay up-to-date!