In the context of rapidly evolving technology, increased workplace flexibility and a global shift towards remote operations, the world is abuzz with the potential of upskilling and re-focusing careers towards data science and cyber security. Although, for most of us wrapping our head around what those fields encompass is hard enough – let alone determining how to break into the spaces, or whether we’d be any good at them.
How is someone with a seemingly irrelevant or parallel experience meant to know what area of data to break into, how to go about it, or even if they should?
Here’s what you need to know to determine which career path is the best fit for you:
1. What’s the difference between data science and cyber security?
In a nutshell, data science’s key objective is to extract valuable insight by processing big data into specialised and more structured data sets. While cyber security protects and secures big data pools and networks from unauthorised access.
To break it down further, cyber security is the practice of protecting electronic data systems from criminal or unauthorised behaviour. The discipline ultimately functions as a preventative measure that defends confidential data and data processes from unwanted breaches. Working in cyber security is well suited to individuals that are curious, have a strong desire to learn and enjoy creative problem solving.
The primary challenges of working in the cyber industry are rapidly evolving technologies, the continuous emergence of new trends, and society’s increasing dependence on digital systems. This means cyber security professionals need to be constantly learning and adapting in order to keep their skills up to date and stay ahead of the curve and potential threats.
Data Scientists on the other hand have a more abstract role as their work isn’t purely focused on analytics or engineering, rather it is a multidisciplinary position that comprises a mix of collecting, extracting, and analysing large amounts of big data from multiple sources. The area requires understanding of artificial intelligence and machine learning techniques such as, support-vector machines, regression, cluster analysis and neural networks.
Additionally, in order to carry out their roles effectively data scientists must be able to drive big data decisions to meet end objectives and solve complex problems. This requires data professionals to master a comprehensive range of technical and analytical skills. People who enjoy mathematics / statistics and have a strong interest in analytics, machine learning, AI and consulting are a brilliant fit for a career in the data science industry.
2. What is big data?
If there is one phrase you are guaranteed to hear on repeat when transitioning into the data industry, it’s ‘big data’.
In most cases, pools of structured and unstructured data are so chaotic that businesses are inundated and bombarded by it daily. The digitally and globally connected world that we live in produces a near incomprehensible amount of data, and buried in this is a wealth of opportunities and solutions. Whether it’s the cure to the common cold, how to live on the moon, or the most effective governance model known to time, it’s sitting there, waiting to be discovered. This is where data science and cyber security come into play as it is the measure of how this data is collated, analysed, stored, protected, and used that has given rise to and shaped these disciplines.
3. What skills do I need to work as a data scientist or cyber security professional?
Known as highly competitive and demanding professions, it is crucial for those wanting a career in data science or cyber security to not simply educate themselves on the theories associated with the professions, but also get knee-deep in practical experience. This will help develop the skills, mindset, and agility needed to excel in these fields.
To work in any area of data, aspiring experts need practical skills training so that they are able to do the job from day one. Unlike more traditional approaches to education, which not only take years but also have a heavy theoretical basis, the fastest way to become trained is through modern industry-focused courses that streamline their content and are geared towards giving students the tools and experience needed to start working right away.
With the data and cyber industry also being so new and progressive, it is important that employers are able to standardise and trust the experience of a potential employee. To achieve this, those wanting to break into the world of data need to have an industry certification. An industry certification in data science or cyber security demonstrates to employers that you have the relevant practical skills to meet their needs and immediately add value.
In addition to learning how to practically apply in-demand tools and techniques on the job, it is also important to have end-to-end project experience. Completing a project demonstrates to employers that an individual is responsible and able to manage real world tasks assigned to them. For example, the Institute of Data’s capstone projects provide a tangible reference for professionals to make during interviews and networking events.
Specifically, when it comes to data science, it is necessary for those working in the area to be able to decipher large data pools, extract data insight, identify trends and patterns using machine learning algorithms, and creatively overcome data obstacles. Data professionals need to have a firm grip of statistics, computational mathematics, machine learning, python programming, data mining, data wrangling, and data analytics and visualisation, in order to solve the highly complex business problems they’ll be tasked with on the job.
A cyber security professional’s skills are centred on intrusion detection, incident response, risk assessment, governance and compliance. There is a lot of ‘black-hat’, or judgement based, thinking required to work as a cyber security specialist. Additionally, cyber professionals equipped with a combination of hard and soft skills such as the ability to strategically plan, produce, perform, test, improve, and solve business security problems, are highly sought-after by potential employers. If you have a more well-rounded mindset towards data, enjoy complicated problem solving, have an interest in security analytics with a desire to protect data and systems from unauthorised access, cyber security is perfect for you.
For both fields, having data intuition and being able to communicate with data is beneficial. It is also generally expected that you have experience using in-demand data tools and software including Python, Linux, C++, Java, SQL, Qlik Sense, Splunk, Yellowfin, Tableau or Microsoft Power BI.
Finally, those entering into the data science and cyber security industry further need to develop their job outcomes focus (e.g. salary negotiation and interpersonal skills), seek career guidance, and build up their industry network. This can sound quite daunting if you don’t have job outcomes support available. All Institute of Data graduates benefit from a Job Outcomes program designed to get them job-ready and working through one on one career coaching, exclusive hiring events, and reverse recruitment opportunities.
4. How do I find a job in data science or cyber security?
It’s one thing to upskill, but how do you actually land a job? In addition to a job outcomes program and the guidance of a dedicated career coach, it ultimately comes down to being seen and being competent.
Here’s 4 steps you can take to accelerate the process of finding a job in data science or cyber security:
1. Attend networking and hiring events: In-person and virtual networking and hiring events are designed to allow certified professionals to meet with potential employers, recruiters and fellow professionals face-to-face. A good way to access these events, many of which are free, is to join the Institute of Data community and professional network or visit sites like Meetup or Eventbrite. Attend these events with confidence, dress for success, and seize any opportunity to secure an interview, or even just an introduction. From here take steps to connect socially and professionally, LinkedIn is a great starting point.
2. Independent research: Keeping your finger on the pulse of new data and cyber trends and what is happening in the industry is one of the most significant distinctions between those who flourish in the data industry, and those that do not. Stay on top of trends by reading the latest data science and cyber security articles and blogs, signing up to newsletters, or listening to podcasts. Don’t feel pressured to learn everything at once. Instead, communicate your ability to stay on top of such trends. Communication will show how passionate and ready you are to start a successful career in the industry.
3. Attend data conferences: Conferences are a fun and unique platform that facilitate important knowledge and relationship exchanges. During conferences you’ll get the opportunity to hear from industry experts and also surround yourself with professionals that have similar career aspirations, and potential mentors that are leaders in the field. This is a great way to build a support network that you can also collaborate with down the line! Your attendance will also reflect a strong initiative and commitment that employers will value.
4. Update your LinkedIn profile: LinkedIn should be used to market your skills, passions, and abilities. However, it is more than just an online resume. LinkedIn is also a powerful networking tool and industry news source. Connect with and follow individuals and companies in your field that you admire or wish to work for, and start engaging and building your professional online network while you apply for jobs!
5. What roles can I apply for once trained in data science or cyber security in Asia-Pacific?
Data and cyber professionals that can meet employer needs will benefit from lucrative job opportunities, fast-tracked career progression and will be at the forefront of technology innovation.
Trained data and cyber professionals are in global demand and there is a lot of versatility in the fields as professionals with existing industry experience and domain knowledge are able to work across industry sectors, and freshers that are able to showcase their practical and soft skills to potential employers are sought-after for entry level positions. Data and cyber professionals in today’s job market have the opportunity to accelerate their careers by out-performing and exceeding employer expectations with job-ready skills.
As a data scientist, career prospects are broader and more creative than many anticipate. There is also huge demand for practically trained data professionals with every business looking to stay ahead of their competitors, understand their customers, and improve operational processes, consumer products and experiences using real-time data insight. Employers are searching for data professionals that possess job-ready data skills.
Jobs you could apply for in data science include data scientist, data analyst, statistician, machine learning engineer, data architect, data engineer, or a data consultant. These roles also have the potential to carry into more senior roles such as a senior AI architect, senior-level director, chief data scientist or a chief information officer.
New opportunities in cyber security are emerging to keep up with growing business needs and an increase in security risks. It is also important to note that the industry is still new and as businesses realise how far technology and data hacking has come, the appreciation of risk mitigation techniques will see more companies start to protect and future-proof their business processes, and new jobs will continue to follow. Currently, cyber security professionals have niche career options in industries like government, security, banking, e-commerce, and privacy law, allowing for a more specialised career path. There are various roles available in cyber security analysis, incident response, governance, risk assurance, and compliance.
Jobs you could apply for in cyber security include cyber security analyst, security consultant, IT security specialist, incident responder, systems engineer, pen-tester, vulnerability analyst, computer forensics analyst, or a cryptographer. These roles also have the potential to carry into more senior roles such as a cyber security manager, information technology director or cyber security officer.
So, should you pursue a career in data science or cyber security?
When thinking about a data driven career path it is important to identify the skills you have, the skills you are willing to learn and your long-term career goals. Consider whether data science aligns with your interests in analytics / statistics and desire to solve business problems using data insight and machine learning tech, or if cyber security connects with your desire to assess and mitigate security risks creatively to protect business data and processes.
Now, take a step back and consider the bigger picture, do you know the answers to the following questions?
- Which area of data am I most passionate about?
- Which technical skills do I perform well / do I have a skills gap?
- How much effort am I willing to put in to expand my job prospects?
- What data related tasks do I see myself enjoying on the job?
- What are my short-term and long-term career goals?
If you would like to discuss your suitability for a career in data science or cyber security in more detail, schedule a call here today.
Learn more: become certified in data science
Learn more: become certified in cyber security