Changing careers can be a taxing experience – but if you plan ahead, do your research (like you’re doing right now!), take the initiative to upskill via an industry recognised course, and keep your cool – you’re doing it right.
1. Our top 3 tips for transitioning your career to data science from Finance / Accounting
It wasn’t long ago, that professionals believed they were destined to progress their careers within the same company they landed their first job in. This was achieved through experience within the parameters of their particular industry and using only what they learned at university.
In today’s rapidly evolving jobs market, your career outlook and progression is no longer limited to one company, one industry, or one set of skills.
Here are our top 3 tips for transitioning your career to big data from a Finance or Accounting background:
- Determine WHY you want to make a career change – what made you choose finance / accounting as your career in the first place? Are you no longer feeling fulfilled by your day-to-day? Are you seeking a better salary? Do you want to challenge yourself professionally? You need to figure out why you want to switch careers because this reason will keep you motivated in your training process, job search, and in your new big data job.
- Determine WHAT you will need to make this career change – you need to objectively evaluate your current skill set and compare it to the skills required for a big data career. Are you willing to fill in any skills gaps and do you have the time to upskill and complete a training program? As a finance or accounting professional you already have many skills relevant for a career in big data, but you must be prepared to upskill your qualifications and learn new skills to suit the needs of the evolving big data industry.
- Determine HOW you will make this career change – so you know why you want to switch careers and what skills you will need. Now, you need to find an educational training program that will enable you to gain practical knowledge and experience in data science and analytics. You will need to choose a program based on the time and monetary resources you have available. Once you have selected a program, stay focused and complete the requirements – refer back to your ‘why’ to keep yourself motivated during this transitional time.
2. How changing careers to big data will help you achieve your career goals with a more rewarding and lucrative career
Wouldn’t it be rewarding to come in to work every day and have the skills to identify consumer insights using data, and help your employer find solutions that improve their revenue and business processes? Well, a career in big data will allow you to do just that, and you will be compensated generously for your in-demand qualifications.
Across all industry sectors, big data careers provide professionals with lucrative job opportunities that are not available to those lacking in data science and analytics skills.
Let’s compare the maximum earning potential of a Finance / Accounting professional to a Big Data Professional in the US, Australia, and Singapore:
Average Salary | Big Data Industry:
- Australia: AUD$126k (an increase of 18% from 2017)
- Singapore: SGD$70k – SGD$99k+ (Averaging AUD$70 – AUD$99k)
- United States: USD$131k (Averaging AUD$181k)
Average Salary | Finance Sector
- Australia: AUD$92k
- Singapore: SGD$51 – SGD82k (Averaging AUD$51 – AUD$82k)
- United States: USD$88k (Averaging AUD$121k)
Average Salary | Accounting Sector
- Australia: AUD$55k – AUD$98k
- Singapore: SGD$41k – SGD$61k (Averaging AUD$41 – AUD$61k)
- United States: USD$63k (Averaging AUD$86k)
3. Here’s how your job description will change and remain similar with the skills required for a successful career switch to big data
As a professional with a background in Finance / Accounting you already possess valuable skills and relevant knowledge required for a job in data science and analytics.
For example, the following qualifications are constantly requested by big data job descriptions, and you already have them!
- Educational background, applied knowledge and experience in mathematics, statistics, finance, accounting, consulting, business analytics, risk management, database administration, financial reporting, and project management.
- Ability to handle quantitative data sets to extract insights, and logically communicate and present statistical findings to key stakeholders to strategically influence business decisions.
- Analytical & softer skills with an aptitude for data, time management and the ability to learn new processes on the job, while working within a team to achieve business and client objectives.
These skills will certainly make it easier for you to make the career switch to big data, but to successfully perform at your new big data job, you will also need to be trained in the following:
- Coding and Machine Learning using open-source data science technologies – Python, R, SQL, Hadoop, Spark, Excel, Tableau.
- Automation Techniques & Predictive Data Analytics – to process large data sets for observation, and to predict patterns and trends from structured and unstructured data sets.
- Data Modelling & Digital Visualisation Techniques – to gather, evaluate, prepare and accurately present quantitative data as well as qualitative and experimental data to clients, to derive data-driven business solutions.
4. The big data industry is actively seeking to hire qualified data science and analytics professionals across all industry sectors
Trained data science and analytics professionals are in high-demand worldwide. In fact, LinkedIn’s Workforce Report found that in August 2018, employers in the United States were seeking to fill jobs with 151,000 data scientists that do not exist in the US.
This growing global skills shortage has opened up job opportunities for big data professionals across all industry sectors, especially in Asia Pacific, where employers are struggling to find qualified professionals to meet the needs of their big data job descriptions. According to a report by the Asia Pacific Economic Cooperation, between now and 2022 – Malaysia, Singapore and the Philippines will need more than 375 000 data scientists between them to fulfil the needs of their job market.
Here are the industry sectors actively seeking to hire data science & analytics professionals in 2018:
- Finance / Accounting
- Food / Beverage
- Engineering / Robotics
- Workforce Management
Data Science and Analytics has had a transformative impact on businesses across industry sectors and improved business processes / products by providing access and analysis of data-centric customer insight. However, although the demand for trained data science and analytics professionals is high, the demand for professionals equipped with a related educational background (finance, mathematics, accounting, business, IT, science, engineering etc.) and a big data skill set, is even higher. You see, with the evolving nature of the big data industry it has become increasingly important for employers, to hire employees that are multi-skilled with a willingness to keep learning and adapting to their data-driven business needs and projects. Read about an Australian CEO’s experience: hiring a IoD data science graduate.
5. Why making a midlife career change to data science could be your sexiest and best strategic career decision of your life
The Harvard Business Review declared data scientist as the “sexiest job of the 21st century” because data scientists have “rare qualities that are much in demand”. This was in 2012. Five years on, the earning potential and demand for qualified data science professionals has exponentially increased, so, why not avoid the midlife financial splurge, re-vamp your qualifications, and make a lucratively sexy career move instead!
To become an in-demand professional half way through your career and meet the growing needs of the big data industry, all you need to do – is amplify your existing skill set. Here’s what will make this the best strategic career decision of your life:
- You will learn new skills and be able to implement them in your day-to-day responsibilities as a big data professional, becoming a high-level value-adding employee while re-energising your career prospects.
- Your earning potential will surge as you progress your big data career because you will possess an in-demand skillset sought after by employers worldwide. They will be seeking you out.
- You will be able to re-activate your career goals and actually acquire the skills, job opportunities, industry status and contacts to achieve them.
In the big data industry, you won’t need to re-start your career journey or wait until you have an excessive amount of experience to become a senior-level employee. If you upskill your qualifications to include data science and analytics training, you will instantly transform your career prospects by becoming the highly skilled professional that’s needed right now by tech companies and SMEs across all industry sectors worldwide. And no, you are definitely not too old to become a data scientist.
It takes courage, motivation, and relevant qualifications to make a successful career transition into the big data industry. This, combined with a high-demand big data job market, will allow you to rapidly progress your career while achieving your career goals.