A report by IDC (International Data Corporation) predicts that the world will handle roughly 163 Zettabytes of data by 2025. It is ten times more than 16 Zettabytes generated in 2016.
The booming field of data science has led to a talent shortage, with companies struggling to find employees with the needed data science skills. However, many companies have started finding creative ways to deal with the drought, by partnering with universities and other organizations to train new employees or by ensuring data teams have better tools and support.
What is the role of a data scientist?
Data scientists use their knowledge of statistics, machine learning, and artificial intelligence to help businesses make sense of their data. They're able to identify patterns in large sets of information that would be impossible for humans to find on their own—for example, they can analyze millions of customer records to determine which customers are likely to leave a company (and when). They also work with business analysts to create reports based on this data that provide valuable insights into how well a company is performing.
In Australia, data scientists typically work in corporate or government settings, providing insights that can guide marketing campaigns, product development, decision-making, and strategic planning. They use various tools and techniques to analyse data, including machine learning, programming languages like R and Python, and statistical software packages.
Why are data science roles in such high demand?
A company is like a human body. It has a brain (management), a heart (employees), and lungs (data). Without any one of these, the company will not function properly. The data scientists are the lungs of the company. They take in all of the information and make sure that it is distributed properly to the other departments. They make sure that the analysis is correct and that the results are accurate. Without them, the company would be like a human body without lungs.
Data science roles are currently the most sought-after jobs in the country, with over 20,000 job openings posted on the popular job search site Indeed in the last three months alone. The demand for data scientists is on the rise throughout the world, and for good reason: these professionals are critical to companies' success.
The ability to collect, store and analyze information is key when it comes to making critical decisions about your business and how you position yourself in the market.
Companies are willing to pay top dollar (the average data scientist salary is $117,645 per year) for skilled professionals who can help them make sense of their data sets and use them as a competitive advantage against other businesses within their industry.
Why is there a shortage of Data Scientists?
The talent shortage in data science is well documented, with numerous articles bemoaning the lack of qualified candidates. There are several reasons why there's a shortage of data scientists in Australia.
For one, it's a relatively new field, so there aren't as many people with the necessary skills and experience.
The demand for data scientists outpaces the supply, making it difficult for businesses to find qualified candidates.
The pay for data scientists isn't always commensurate with the demands of the job, which can dissuade people from applying to any company less than an MNC.
Seven strategies to maximise your data science pool
The following are seven primary methods companies can use to optimise their data science talent pool. Let’s take a look at them:
1. Training and development of current employees
The talent shortage is a genuine global issue for companies, and it's only getting worse. While there are several ways to address the problem, one of the most effective methods is to focus on enhancing the skills of existing employees.
This can be done through online courses, in-person workshops, or even simply by sending employees to conferences and webinars. By giving employees the tools they need to succeed, you can help them reach their full potential and make a real impact on your business.
Of course, training is just one piece of the puzzle. You also need to create an environment that encourages learning and growth. This means giving employees time to experiment and test new ideas and providing constructive and positive feedback. When you create an environment that nurtures talent, you'll be amazed at what your team is capable of achieving.
2. Ensure data teams have better tools, processes, and support
Start investing in better tools for your data teams. This includes software tools that make data analysis easier and hardware that can handle large data sets.
Another way to address the talent shortage is to improve processes. This includes streamlining data collection and ensuring that data is properly labeled and organised.
Finally, companies must ensure that their data teams have the support they need. This includes both technical support and managerial support.
3. Offer networking and mentorship for new data scientists and partner with schools
Many companies have started offering networking opportunities and mentorship for new data scientists. For example, they may partner with schools to offer data science courses or host events where data scientists can meet and learn from each other.
Some companies also offer mentorship programs to help new data scientists transition into the field and gain the skills they need to succeed. By taking these measures, companies can attract and retain the talent they need to stay competitive in the ever-changing world of data.
4. Outsource work to a data science consulting firm
Data science companies are able to provide you with an entire team of highly-skilled data scientists who can help you optimize your data science processes and make sure that you're getting the most out of your investment.
You can trust these firms to hire only the best candidates, because they know how important it is for them to be able to offer their clients only the highest quality services.
They'll also be able to give you advice on how best to handle your specific challenges in order for them to be resolved as quickly as possible.
5. Provide transparent career road maps & relaxing work-culture
By providing transparent career road maps, companies can demonstrate their commitment to developing their data science teams and attracting top talent.
Data science is a competitive marketplace. It’s the talent that can make or break a company. So, how do companies provide transparent career road maps and attract top talent? Some companies offer employee stock ownership plans, flexible work hours, and on-site child care.
Others focus on creating a fun, relaxed work environment with ping-pong tables and game rooms. And then there are the companies that offer unlimited vacation days, free massages, and catered lunches. No matter the perks, companies should strive to create an environment that will attract & retain top talent.
6. Create a clear and recognisable voice for your brand
By creating a solid and distinct brand identity, employers can attract the attention of potential employees who share their values and vision.
In addition, a well-defined brand voice can help to build trust and rapport with potential recruits, making them more likely to submit an application or accept a job offer. In today's competitive market, developing a strong brand voice is one of the most effective indirect recruiting tactics.
7. Hire workers remotely
Remote workers allow companies to hire the best and brightest talent without having to provide them with a large office space or other perks.
In addition, by hiring remote workers, companies can save money on office space and other overhead costs. According to Global Workplace Analytics, six out of ten employers say telecommuting reduces costs.
If you have an office in multiple locations, it is often cheaper to hire remote employees who work from home rather than paying for office space in each location.
To sum up:
These are all viable solutions for the time being; however, as the demand for data scientists continues to grow, the competition for these talented individuals will become even more significant. Businesses need to start planning how to manage when the data science talent shortage becomes even more severe.