In today’s world, whatever your job, having skills and knowledge in Data Science will play a huge role in your career development. For example, big data and analytics gathered from customers allow marketers to build more effective digital marketing campaigns.
Elsewhere, city planners are gathering huge reams of data about how people move around the city and using it to help build building ‘smart cities’ that will run faster and more efficiently.
Retail has been upended by Amazon thanks to its data driven logistics capabilities. Amazon uses data to keep a tight hold on its mammoth inventory, but still ensure there is enough stock at each of its warehouses to guarantee consumers get their products rapidly after ordering online.
Healthcare is also being revolutionised by data, and urgently needs more Data Scientists.
With the increasing digitisation of patient records, healthcare experts are finding new ways to make more accurate and time-sensitive diagnosis while simultaneously being under extreme regulatory pressures that mean the data needs to be handled with incredible sensitivity.
Healthcare organisations are looking to Data Scientists to build the foundation and structures around the handling of this data.
And for an example of how data analytics is changing the way sport is played, read Michael Lewis’ 2003 book, Moneyball, which describes a team that went from being one of the poorest, most underperforming in its league to eventually become the champions. It’s an inspirational story that is underpinned by a management team which saw the value of data.
“Data Scientists are in high demand and the projections in the short term are not different,” James Cook University course coordinator, Ricardo Campello, said. “A qualified Data Scientist excels a core collection of interdisciplinary skills that comprise the whole lifecycle of data.
They are trained in a blend of computing, mathematics, statistics, and business oriented topics that allow them to work alongside domain experts in virtually all fields. In my opinion, the interdisciplinary background is the most significant asset added to one’s resume.”
For more information on the variety of places a career in Data Science can take you, read this blog.
With every industry and sector now looking to data and analytics to drive competitive differentiation, people with Data Science qualifications are in huge demand and there are many career opportunities available. In fact, across the Asia-Pacific region, only one-third of Data Science jobs are currently being filled. This means:
1) You are in demand – in addition to being able to apply your skills to any sector, you can continue to work in Australia, or pursue work overseas, knowing that in the majority of countries you visit, Data Science skills will be high on the list of priorities for organisations.
2) The pay is good – the demand for good Data Scientists means that earning expectations are high. Deloitte research shows that by 2021-2022, the forecast income of data scientists with postgraduate qualifications will be $130,176.
Additionally, with the increased role of automation, machine learning, robotics and AI, many of the more menial jobs are being replaced by technology. Data Science is an opportunity for professionals to move up the value chain and find work opportunities in areas where machines don’t have a role. “We all know that automation didn’t bring any chaos and threaten society by taking millions of jobs,”
Campello said. “Instead, it mostly replaced dangerous or tedious jobs with others that require qualification and more sophisticated skills. From this perspective, automation can be an opportunity, rather than a threat. Artificial intelligence and machine learning are building upon the digital revolution and are bringing another wave of automation. Having qualification and skills in this area can certainly give professionals a competitive advantage.”
There are plenty of other benefits to having Data Science skillsets. They are outlined in this video “What excites you about Data Science?”
What do I need to be a data scientist?
People with a background in IT, maths, computer engineering or engineering generally find a Master in Data Science to be a natural extension of their existing skillsets, but they are not the only backgrounds that benefit from the degree. As previously discussed, everybody from marketers to executive management benefit to some degree by having an understanding of Data Science.
To participate in James Cook University’s Master of Data Science degree, you will need a relevant Bachelor degree or at least five years of work experience in an IT or Data Science related industry. This is to ensure you have the base level skillset to manage the coursework, which has been specifically tuned to develop skills, including:
- Programming: Data Science involves a lot of coding in languages such as MATLAB, Python, Hadoop and SQL. Having an understanding of these languages is important in getting the most out of any Data Science initiative you might undertake in your professional career.
- Quantitative analysis: Here you will learn about data visualisation, data mining, statistical methods and database systems.
- Product intuition: You will also learn about how data can be used to inform product development and iteration decisions, in order to better deliver what the consumer wants.
- Communication and storytelling: Being able to present the data to key stakeholders in a way that cuts to what the core of the data is saying is a critical skill for a Data Scientist
- Teamwork: Data Science initiatives are generally all-of-business affairs. It is important a Data Scientist works with stakeholders both within his or her own department, and those outside.
How a Master in Data Science will develop those skills
A Master in Data Science spans the foundations of Data Science, strategic thinking, management, and real-world complex applications.
In addition to what is mentioned above, students learn model diagnostics and advanced data querying, culminating in the production of capstone projects, where they solve complex data-driven, problems relevant to either industry, science, government or the social environment.
On completing these projects, students will have a portfolio that confirms their Data Science skills to potential employers.
Attention Agile Programmers: Project Management is not Software Engineering
As the course is taught online and part-time, it is an ideal option by which professionals can broaden their skillsets without ignoring existing career development. It can be completed in as little as two years, making it an efficient way to also further develop capabilities, and have those demonstrable Data Science skills available as peak demand for the profession hits.