Cybersecurity vs. Data Science: Which Career Path Is Right for You?

Table of Contents

• [toc headings="h2,h3" title="Table of Contents"] Data science and cybersecurity are adjacent and similar careers, and both types of professionals are in high demand in today's business world. They also use similar skill sets, with both types of professionals needing a sharp eye for detail, a mind for creative problem solving, and in-depth knowledge of computer systems and programming. This makes both career paths appealing for students and tech professionals looking toward their future. Let's take a closer look at how these two fields differ and how to build a successful career in each.

• Cybersecurity and data science defined

• Cybersecurity and data science are closely related fields. Both use technology and data to maintain or improve how an organization functions. The difference comes down to how they use these tools, which skills they need for the role, and what solutions the role delivers to companies. A concise definition of cybersecurity is that it's the practice of protecting hardware, networks, and systems from digital threats and attacks. These attacks are often aimed at accessing or destroying sensitive information, interrupting the business' operations, or extorting individuals and organizations through ransomware. To do this effectively, cybersecurity professionals need an in-depth understanding of the devices, software, and networks they're protecting, as well as the tools and methods used by hackers to access them. This requires knowledge of programming languages, operating systems, and security trends and best practices. While security professionals often analyze data and code, it's with the aim of identifying vulnerabilities and breaches more than deriving insights from them. Data science is the practice of studying and analyzing data in order to interpret it and derive meaningful insights organizations can use to improve their processes or better serve their customers. These professionals use statistics, algorithms, computing, and other data mining approaches to make sense of large and often noisy data sets. Roles in data science usually require at least a working knowledge of machine learning and artificial intelligence, as well as a strong foundation in big data and data analytics.

• Education for data science vs. cybersecurity

• Job seekers will typically need at least a Bachelor's degree to start a career in either data science or cybersecurity, and a Master's degree may be required for senior-level or management roles in both industries. Each field has dedicated degree programs students can pursue. Majors in cybersecurity or information security are offered at both the undergraduate and graduate level by many universities across the United States. A major in data science is less common at the Bachelor's level, though these programs have been increasing in number, both in on-campus and online programs. Data scientists can also get a MS in Data Analytics or Data Science to support their progress into leadership roles. While there are dedicated degree programs for both these fields, there are other options. A Bachelor's degree in a field like information technology, network administration, computer science, computer engineering, or computer programming can also provide a foundation of skills and knowledge for cybersecurity professionals. You'll find a similar array of options for data science jobs, with computer science, statistics, mathematics, and information technology among the most common majors. As you can see, there is some overlap in the types of degrees that can help an individual get hired in these fields. For someone who isn't sure yet what area of the technology industry they want to get into, a more general IT, computer science, or programming major can keep your options open. You can then add to your training by obtaining certifications after you've made a decision about the specific career path you want to pursue.

• Data science certifications

• In addition to a college degree, many data science professionals obtain certificates to verify their skills and knowledge for employers. There are a variety of certifications to choose from. Which one is right for a given professional will depend on the specific job opportunities they're interested in. The following are popular vendor-neutral certifications for data professions:

  • Certified Analytics Professional (CAP) - CAP certification validates the ability to transform complex data into valuable and actionable insights. This certification is designed for experienced professionals, and you'll need 3-7 years of experience to qualify for the exam, depending on your level of education.
  • DASCA Senior Data Scientist (SDS) - Ideal for data analysts and data engineers who want to move into more senior data science roles, this training program has five tracks for candidates depending on their specialty and the stage of their career. The topics covered include statistical analysis, databases, R, quantitative methods, and object-oriented programming. A minimum of five years of experience is required to qualify.
  • DASCA Principal Data Scientist (PDS) - This is the more advanced of the two DASCA certifications, and is intended for professionals with at least 10 years of experience. It covers advanced topics like big data best practices, machine learning, scholastic modeling, and business data strategies.
  • Open Certified Data Scientist (Open CDS) - The most comprehensive certification available for data scientists, this is an experienced-based certificate, with no courses or exams. It's available in three levels (Certified Data Scientist, Master Certified Data Scientist, and Distinguished Certified Data Scientist) which are obtained by completing an experience application form and passing a board review.
  • SAS Certified AI and Machine Learning Professional - This certification validates a candidate's ability in using AI/ML principles to gain insights from data. To obtain it, professionals need to pass multiple exams on topics such as natural language processing, model forecasting and optimization, computer vision and machine learning.
  • SAS Certified Advanced Analytics Professional Using SAS 9 - Earning this certification demonstrates a candidate's big data, statistical analysis, and predictive modeling skills and knowledge. Getting certified means passing three exams, and professionals should have experience in areas like pattern detection, time-series forecasting, business optimization, and distributed data sets before registering for the test.
  • SAS Certified Data Scientist - This combines the previous two SAS certifications, covering topics like data manipulation and transformation, data management, data visualization tools, and programming. It's earned by completing the 18 courses and five exams of the Advanced Analytics Professional and AI and Machine Learning Professional certification programs.
  Along with these vendor-neutral certifications, there are several certificates for data scientists that demonstrate expertise with specific systems or software. These include Microsoft Certified: Azure Data Scientist Associate, IBM Data Science Professional, and Cloudera Data Platform Generalist, to name the most popular options.

• Cybersecurity certifications

• Just like with data science, people who want to get into cybersecurity can enhance their application by obtaining certification. These range from generalist certifications that cover a range of cybersecurity topics to more specialized training for specific job titles and career paths. The most popular general cybersecurity certifications include:

  • Certified Information Systems Auditor (CISA) - Obtained through the professional organization ISACA, this credential is one of the most recognized for security auditors. It shows expertise in assessing vulnerabilities, implementing controls, protecting information assets, and reporting on compliance. Three to five years of IT experience are required, depending on the student's level of education.
  • Certified Information Security Manager (CISM) - Also obtained through ISACA, this credential is ideal for IT managers. It includes general topics like risk management and incident response, as well as more advanced concepts like program development and governance. Qualification requires five years of experience, though two can be waived with a graduate degree or another certification.
  • Certified Information Systems Security Professional (CISSP) - Offered by (ISC)2, this credential verifies the ability to design, implement, and manage an organization's entire security infrastructure. It's mostly valuable to senior-level professionals, such as security architects, security managers, and IT directors. A minimum of five years' work experience is required to register.
  • CompTIA Security+ - This entry-level certification verifies the fundamental, practical skills professionals need for an information security career. It demonstrates an ability to assess an organization's security in networked, cloud, mobile, and IoT environments, respond to incidents, and understand regulations regarding risk and compliance. Two years of experience are recommended but not required.
  • GIAC Security Essentials Certification (GSEC) - Another entry-level credential, this exam tests knowledge of network security, cryptography, incident response, cloud security, and other fundamental cybersecurity knowledge. It has no experience requirement, making it ideal for those just getting started in the industry.
  • Systems Security Certified Practitioner (SSCP) - This certification from (ISC)2 is designed for IT professionals who work directly with a company's data assets and security systems. It shows expertise in network, system, and application security, as well as skills like cryptography, security administration, access controls, and incident response. One year of work experience or a degree is required to qualify.
  There are many other cybersecurity certifications available for specific job titles within the industry. For example, penetration testers may consider Certified Ethical Hacker (CEH) or Offensive Security Certified Professional (OSCP) credentials, while those on the investigative side will be better served with a Certified Digital Forensics Examiner (CDFE) or GIAC Certified Forensic Analyst (GCFA) credential.

• Do data scientists or cybersecurity professionals earn a higher salary?

• This is a tricky question to answer accurately, since the salary of a data science or cybersecurity professional depends on factors like their experience level, specific role, and location. However, both fields offer a high salary potential. At the entry level, data scientists tend to earn a bit more than those in cybersecurity. The average salary for an entry-level security analyst is around $63,000 per year, while the average entry-level salary for data scientists is around $86,000 per year. One of the benefits of a career in cybersecurity is that average salaries rise quickly. Once a cybersecurity employee has accrued around five years of experience, they can expect to earn upwards of $88,000 per year, and senior professionals with 10 or more years of experience typically earn a six-figure salary. The average salary of an experienced data scientist professional is comparable, ranging from $97,000 to $108,000 per year. Now, salaries can certainly go much higher than that, particularly once you get up into upper leadership and executive roles, but the same is true of cybersecurity. The bottom line is that you can earn a very comfortable living in either career path, and you won't have to spend too long working in the industry to get there.

• Job outlook for data science and cybersecurity

• Individuals and organizations today use a wider range of technologies, and more technology overall, than ever in the past. There's no sign that trend will reverse any time soon, either. This has driven significant growth in both the data and security sectors. Something else these two industries share: neither workforce has kept up with the increase in demand, leaving a significant amount of roles unfilled in each discipline. According to the U.S. Bureau of Labor Statistics, there were more than 113,000 data scientist jobs across the country in 2021. That number is expected to grow by 36% by 2031, which is significantly faster growth than the 5% predicted for the overall job market. The numbers for the cybersecurity industry tell a similar story. The unemployment rate for cybersecurity professionals has been at 0% since 2016, and the BLS reports similar employment figures for security analysts as for data scientists, with 163,000 current openings and an anticipated growth rate of 35% through 2031.

• Career paths and work environment

• One reason that data scientists and cybersecurity professionals are in such high demand is that they're needed in a variety of industries. From the technology industry to companies in finance, healthcare, retail, and the public sector, any company that could face the threat of cyberattacks needs a security team to prevent them. The need to gain insight from data is equally pervasive across sectors. While they can work in a range of industries, though, the day-to-day work environment is similar. In the case of both security and data workers, they normally work in an office setting with a typical 9-5 schedule, though remote and hybrid positions are widely available in both fields. In both cases, their daily duties are often autonomous and independent, though they often do work as part of a broader IT, data, or security team. Both types of professionals may work directly for companies, for a consulting firm, or as a freelancer or independent contractor. One notable difference between these career paths is that cybersecurity has potential to be a much higher stress environment. This is particularly true for those who work in incident response. Attackers don't always wait for standard business hours to make their attack, which can mean being on-call at nights or on the weekends. Other roles in cybersecurity aren't as time sensitive, however, so professionals can find a flexible or low-stress job in either industry.

• Common cybersecurity career paths

• Penetration tester

• Average salary: $86,000 per year Feeder roles: Network administrator, IT analyst, IT auditor Also called vulnerability testers or ethical hackers, penetration testers use hacking techniques to identify security weaknesses. Junior penetration testers are a mid-level role in the cybersecurity field, typically requiring about five years of experience. More senior penetration testers often take on a leadership role, managing junior analysts and auditors.

• Cybersecurity engineer

• Average salary: $95,000 per year Feeder roles: Security analyst, IT auditor, penetration tester Security engineers develop, design, and implement security systems and solutions for companies. This starts by analyzing the network and systems for vulnerabilities, then developing defenses against malware, hackers, insider threats, and other types of cybercrime.

• Cybersecurity architect

• Average salary: $128,000 per year Feeder roles: Penetration tester, network engineer, security auditor As you might guess from the name, architects build and maintain the security infrastructure for an organization. This normally involves managing a broader team of penetration testers, auditors, analysts, and specialists who identify vulnerabilities and implement solutions under the guidance of the security architect.

• Common data science career paths

• Data engineer

• Average salary: $94,000 per year Feeder roles: Data analyst, software developer, junior data scientist Engineers create and manage the data pipeline for an organization. They also develop new solutions for analyzing that data. A subset of this role is the big data engineer, who designs and implements the algorithms and modeling techniques the data team uses to derive insights.

• Data architect

• Average salary: $119,000 per year Feeder roles: Business analyst, database administrator, machine learning analyst Similar to security architects, data architects develop and maintain the entire data infrastructure. They may design new analytic approaches or adapt known strategies to the specific needs of their organization. This is often a leadership role that oversees a broader data team.

• Director of analytics

• Average salary: $139,000 Feeder roles: Senior data scientist, data architect, data engineer Directors oversee the entire data strategy and team for an organization. Similar job titles include Insights Director, Data Strategy Manager, or Director of Business Intelligence, all of whom oversee the team responsible for gathering, manipulating, and interpreting data.

• Choosing your ideal technology career

• The recent wave of tech layoffs has many professionals questioning whether the tech bubble has burst. Even through these disruptions, however, data and security roles have remained in high demand, and it's likely they'll continue to see a bright job outlook for at least the next decade. Now that you understand a bit more about how these fields are related, where they differ, and how to build a career in each area, you can decide which area is your best fit.