What to Expect From a Career in Data Analytics: Market Trends and Salaries
Data analytics and business intelligence – a career for life?
Well, so long as the world spends more time online than offline, data will play a significant role in our lives... Here’s an overview of data analytics and business intelligence careers, salaries, and the current hiring market.
In this guide:
Data analytics and business intelligence in a nutshell
“If you're not paying for the product, then you are the product.” This quote from Google’s former design ethicist, Tristan Harris, clearly explains the power of data in our lives, today. Data has been described as the new oil, with the key to potential being its ability to unlock billions of dollars in revenue.
Sounds a bit off-putting – like a sunny Queensland street on bin day. However, data analytics can answer critical business questions by using advanced techniques in statistical modelling with what is now known as data science and machine learning. Analytics teams often hold billions of rows of data for deep-dive analyses – known as data mining or data wrangling – to build a narrative that can relay this key information back to stakeholders: AKA data storytelling.
There are several common functions for analytics in businesses:
predictive analytics to drive business decision making
targeted advertising and personalisation
algorithm development for automation.
The profession has seen huge growth over the last five years. “Data Scientist” has even been voted the number one “coolest” and most sought-after job title on several occasions since 2017!
The most in-demand tools and languages for data analytics roles right now
While there are many tools and languages that can be used, these are the most demanded requirements we’re seeing (that are attracting the best pay rates to match):
SAS – less common, but many large businesses have this in their legacy systems
Tableau, Power BI, and other data visualisation tools
a degree in mathematics, statistics, computer science, or machine learning-based disciplines
MSc or Ph.D. level is often required for more programming centric roles
demonstrable experience – businesses expect to see practical application of real-world analytics, not just theory!
Sidenote: Python was one of the most searched terms on Google last year and in 2020, proving its popularity.
What to expect from a career as a DA and BI professional
Data is quite possibly the most exciting industry to be in, in the modern world! Data is everywhere and is used by businesses to make decisions at every minute of every day. A career in data means solving real-life problems by flexing your mathematics muscles and continuously finding new and innovative ways to approach the complex questions asked of you.
The best analysts will need to be competent at analysing vast amounts of data sets – known as Big Data. And the very best analysts will need to analyse this data and clearly relay back to the business what it means by identifying patterns and trends that no one else can see.
Top analysts will be able to answer why and propose innovative solutions going forward.
In Sydney, much of the demand for data analytics is in financial services and retail. Westpac, for example, have huge data teams across multiple areas of the business (credit risk, marketing, governance, group strategy [consulting], remediation, and advanced analytics), which creates a valuable opportunity for people coming in at all levels and across skill sets. Their training and development programs are excellent, and you’ll be surrounded by both experienced analysts and top-level strategic thinkers.
Companies like Woolworths and AWS, for another example, have a strong foothold in data science and machine learning with a focus on customer analytics.
Market insights and hiring trends
The main challenge in this market is the demand and competition for true, highly skilled talent and relevant technical skillsets. Demand is amplified by a skills shortage where a more advanced level of commercial experience is needed.
Given the demand, we’re seeing a rapid increase in hiring process speed. Most recently, a tier-one, top consultancy arranged a three-stage interview process in one day, just to secure their candidate!
Companies are really focusing on their data journey now. We’re seeing big investment from CEOs to put data at the forefront of their hiring, which is not just exciting news, but essential to keep up with the market. The main challenge is identifying each company’s unique needs and business questions.
Additionally, I’m getting an influx of people asking about full-time WFH / remote working options, in combination with a huge rise in people moving up north (particularly NSW and Victorians migrating to southeast Queensland), that’s been placing a huge demand on rentals up there. Not specifically related to data roles, but a clear sign that remote working and salaries will be a competitive edge for businesses seeking such highly demanded talent.
Data analytics salaries in Australia
Salaries have been booming for analysts and data scientists. Like any economy, it’s critical to keep up with the ever-changing fluctuations of supply and demand. With the pandemic having an even bigger effect on interstate and international travel, the strength of the data market continues.
However, the investment in an experienced, capable, hard-working data analyst is minimal compared to the financial return they bring to the business.
Typical salary ranges:
Entry $60K - $80K
Junior $80K - $120K
Mid $120K - $150K
Senior $150K - $180K
Lead $180K - $250K
Manager/Head $250K - $300K
Chief Data Officer $300K+
How to start your career in data analytics and business intelligence
By nature, the profession of data analytics (by way of technology), is always evolving and adapting, so there are always new courses and learning tools available. The traditional route through university is the logical first step from school, but in today’s world, you’ll also find endless online courses to suit every passion, not to mention things like YouTube for the basics in coding.
Our advice, however, is to get into the industry as soon as you can after your academic studies from university. You’ll learn more in one month by sitting in and amongst a team of experienced analysts than you will in three years of study! The data sets are real-world, and the business questions are engaging, fun, difficult, challenging, and always changing. The data will be messy and there will be critical deadlines to keep the ship sailing, keeping you on your toes and adapting quickly.
The greatest thing about a career in data is the fact it is so transferable. That’s because almost any industry, of any size, anywhere in the world, uses data. You’ll be able to transition easily from Consulting into Financial Services into Retail into Telco into Tech – from huge businesses with teams of one thousand analysts to Silicon Valley tech start-ups operating from the basement.
Data really is a vertical, niche industry where, as long as you know the value it brings, you’ll have a job for life.
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