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Demand for data.

Fiona Gilfillan • Nov 29, 2023

The rise and rise of the data team.

Have you noticed your data team slowly expanding their presence in the office? The rise of the Data Scientist has been a phenomenon over the last few years with demand rising with the explosion of AI and machine learning. Data Science is now amongst the top 5 in-demand jobs in Australia.

 

So what does a Data Scientist do? 

Data Scientists are responsible for analysing large sets of data and creating insights based on analytics. Their findings may inform critical business or marketing strategy. We’ve spoken to a number of current practitioners to gain insight into life as a Data Scientist to understand the importance and power this role plays.

 

What’s driving the demand for Data Scientists?

The focus on customer data and the sheer volume of data collected and retained by companies has meant an increased need for people who can make sense of it all and build actionable insights and business strategies. It’s opened up a world of opportunity for people with these skills. Whereas there’s traditionally been a need in pharmaceutical, finance and market research, there’s now demand from retail, advertising, media and even sports. Data Scientists can work across a diverse range of industries and apply skills across a broad range of challenges, which is very appealing for candidates. Australian Data Scientists are also in-demand internationally as data regulations and programming languages are remarkably consistent across countries. Whilst we saw a large volume of data experts leave our shores during covid, the numbers are now building with a heavy reliance on skilled immigration.

 

What’s the typical pathway for a Data Scientist?

Traditionally Data Scientists came from a background of mathematics, economics, statistics or finance but increasingly there’s a new generation coming from computer science or analytics. Many candidates complete a Master of Data Science or Master of Computer Science to enter the industry and will be skilled across Tableau, SQL, Python, R, Power BI. On top of technical skills, a Data Scientist must have curiosity and imagination to ask the right questions and build innovative solutions to problems. They must also have strong communication skills to effectively communicate insights and findings to the business.

 

What do Data Scientist’s love about their work?

Data Scientists are passionate about what they do. There’s scope to be creative and innovative, design experiments and solutions to deliver real business value. There’s also abundant variety in the work – projects change frequently and skills can be applied to a wide range of data sets and different organisations.

 

Is there a shortage of females in the industry?

At the moment female Data Scientists are in the minority but this is changing quickly. It’s an industry where progression is merit based and the gender pay gap is low. As one senior female Data Scientist said “others in the profession care far more about the elegance of your code than whether you are wearing a skirt or pants”.

 

What benefit does a Data Scientist bring to an organisation?

More companies are realising success as a result from more data driven strategies and approaches, and a good data scientist will deliver a deeper understanding by asking the right questions and providing solutions to those answers. Many organisations are just beginning to realise the power of their data and beginning their data science journey  - and the role will evolve and grow with this journey. There’s opportunity for Data Scientists to influence across strategy, capability and innovation.

 

What should aspiring Data Scientists consider?

A background in analytics and mathematics can be a ticket to an exciting and rewarding career. Aspiring Data Scientists should consider getting a mentor, attend as many meetups as possible and participate in collaborative projects to broaden their experience. The path to the top can take patience. There’s a huge component of unglamorous ‘grunt work’ to prepare data and set up environments for modelling. You need to do the groundwork of sorting, prepping and interrogating the data in order for elegant solutions and complex models to actually work, but the pay-off in the end is a career that can really take you anywhere! The rise of AI will also push Data Scientists to analyse data and make business suggestions and operational improvements so more focus on problem solving and application in the future.

 

 

 


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