If you have been looking for ways to revitalise your career or make a change, the talk around data science and the important role of data scientists in many industries may have caught your attention. However, without a new degree or time out of the workforce, it might seem that a career path adjustment is too risky of an investment for a well-established professional.
However, there’s no reason why individuals can’t begin work in data science later in their careers. In fact, it may even have its own unique benefits. Read on for five reasons why there’s never a wrong time to learn data science.
1. Becoming a data scientist mid-career is a common occurrence for many
There are some careers that most professionals begin preparing for quite early in life. For instance, if you want to become a doctor, your training can take more than a decade, so you will most likely need to begin working towards your qualifications from a relatively young age.
Data science, however, is different. First, it is a relatively young discipline. For many individuals who “got in on the ground floor” in data science, there was no such thing as a data scientist role when they first began their careers. Second, data science is a tool that can be used in many different industries, so niche expertise and experience is often an asset. Taken together, these two factors have resulted in many people turning to data science in the middle of their careers, as the discipline presents new opportunities for them to apply their existing skills.
2. Increased earning potential makes pursuing data science training worthwhile
Unlike many career changes that can be both expensive in the short-term and risky when it comes to their long-term payoff, data science is almost always a lucrative choice for qualified professionals. There are many short and efficient ways to study data science online, such as the Fundamentals of Data Science (Technical) course we offer at Southampton Data Science Academy, that reduce the opportunity cost of taking time away from the workplace for training.
Additionally, according to data from tech recruitment website Hired, the average salary for a data scientist can be as much as £67,000, and demand for qualified individuals to fill these roles is higher than ever. If you are interested in becoming a data scientist, you do not likely have to worry about it being too late to be worthwhile financially – with efficient training and lucrative job prospects, a data science career is a timeless opportunity.
3. You can use your existing quantitative skills to study data science online
Data science is a new and distinct discipline, in which professionals gain new levels of insight from data through different processing, cleaning, modelling, and visualising techniques. The common quality that all data scientists possess, regardless of their academic or professional background, is strong quantitative skills. These strengths – often in math, statistics, and computer programming – are what make data scientists so valuable.
Earning these skills is the most difficult part of becoming a data scientist. If you already have them, learning to leverage them in the data science process is a formidable but very achievable task. If you have advanced qualifications, experience, or degrees in a quantitative subject, you do not have to completely change career tracks to become a data scientist; you only have to learn a new way to apply your skills.
4. You can apply data science to your current role
While becoming a data scientist can be an incredibly rewarding career shift, you don’t need to completely move away from your existing job if you’re passionate about what you do. As mentioned earlier, data science can be applied to a vast number of industries.
The knowledge you gain from studying data science, combined with the industry expertise you already possess, can substantially reshape the approach you take to your work. By utilising your proficiency in both subjects to explore new processes and applications for the data in your field, you could create new opportunities to progress further within your organisation.
5. Studying data science is itself a commitment to lifelong learning
Data scientists are constantly learning, regardless of their age or how long they’ve been in the profession. After all, the tools, techniques, and frameworks organisations use are evolving all the time; the relatively recent arrival of Data Scientist as a profession is proof in itself of that.
Therefore, anyone in data science needs to be able to keep up with this high rate of change in order to stay competitive. Being attune to such developments is how a data science professional can truly benefit the team they are a part of or the projects they work on. By embracing constant growth, you embody what many would argue is a key quality to succeeding in the field.
If you’re considering a career in data science, our CPD-accredited courses might be an excellent fit. Study online and part-time, without having to sacrifice your professional or personal commitments:
