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Why Data Science Needs a Solution to the Talent Shortage

5 mins

Data Scientist jobs were once quoted as “the sexiest job of the 21st Century” by the Harvard...

Data Scientist jobs were once quoted as “the sexiest job of the 21st Century” by the Harvard Business Review. Fast forward to now, and the demand for talent in the field has never been more sought-after, but simultaneously, there are growing reasons why data science talent has never been harder to find. 

In 2017, IBM predicted there would be nearly 3 million open data scientist jobs in the US alone by 2020. With the pandemic being something they could not predict, the demand for data science skills is expected to rise by almost 28% by 2026

Additionally, Anaconda's State of Data Science 2022 report states that 90% of professionals are concerned about how the data science talent shortage will impact their organisations. But why is data science talent so scarce?

Ultimately, the reason why data science talent is so hard to find is because of a supply and demand issue and how new and niche data science careers are. Today, you will struggle to find specialists with more than 30 years of experience. Without a specialist network of professionals, you'll be lucky to find anyone with over ten years of experience. 

Big Data and AI Solutions 

Businesses can tackle the talent shortage in data science and still get the resources needed for data analysis by using tools like Artificial Intelligence (AI). To that end, companies can sift through massive amounts of data and help gain information that could aid critical decision-making.

Thanks to the advancement of technologies, the capability of AI has improved within the same timeframe. In addition, the increased computational and analytical power means that AI can now complete more tasks in record time without requiring human involvement.

While some may see AI as a threat to the current state of employment, the fact is AI is also creating new exciting opportunities. According to a World Economic Forum (WEF) report, 85 million automation and technology jobs are expected to be displaced, but the same deep learning technologies will create 97 million new roles by 2025. AI will simply reshape many current technology jobs from manufacturing to production lines.

This data science AI solutions approach will allow businesses to focus on creating and improving higher-priority tasks or projects that rely on niche human abilities. Particularly in the data science industry, it would mean that companies can utilise their resources more effectively and maximise the benefits.

Find Talent With Transferable Skills

Deploying AI to undertake routine data mining is one way to help businesses combat a general lack of resources in this area, but there are other solutions.

Another option for businesses to address the need for data scientists is to recruit further away from the traditional job markets in fields with similar skills. Although it's more common for companies to hire professionals with a background in data science, recruiting outside this scope will widen a narrow range of available candidates.

Professionals working in similar roles but in different markets can transfer their skills from one sector to another with minimal disruptions. The added benefit of this approach is that it can offer a new perspective and challenge common understandings or assumptions that, in turn, translate into valuable systematic insights.

Undoubtedly, hiring further from the sector can pose challenges to most human resource teams, especially if the role is highly-technical. In this instance, businesses can seek support from recruitment consultancies specialising in hiring and recruiting niche skills. Unlike in-house HR divisions, specialist recruitment consultancies who work across multiple industries have a unique understanding of what is and isn't a transferable skill.

Data science training for talent with transferable skills 

In terms of difficulty, retraining professionals from different data science backgrounds may prove far too complicated and expensive for most companies. Retraining requires a long-term overview of the organisation to implement skill transformations effectively while keeping up with the demands and advancement of the business.

Due to data scientist jobs being relatively new career paths with a limited talent pool, businesses must train talent with transferable skills to ensure they stay caught up with the competition. As the technology sector evolves rapidly, waiting for emerging talent and graduates to gain the skills and experience needed to fill your data science positions is not an option if you intend to thrive in the busy market.

From a hiring perspective, recruiting data scientists and those with similar skill sets is a relatively straightforward process. But hiring and retraining professionals from other backgrounds will require a different strategy. Organisations who wish to adopt this approach can manage this challenge by seeking support from recruitment consultancies with experience across multiple sectors. 

Upskilling existing data science talent

Upskilling is a rising trend in many industries and plays a significant role in future-proofing workforces. But to upskill data science talent, businesses must first identify and qualify the individuals in their existing workforce who would benefit from upskilling.

Modern software like data analytics and dashboards offer organisations and business leaders the chance to empower the visibility of skills, which can be used to understand upskilling needs. Here, technology plays a vital role, and businesses must commit to adopting an agile model that ultimately invests and integrates modern learning and development cultures.

A survey by SAS revealed that 25% of key business decision-makers are hesitant to offer upskilling opportunities to their talent as they fear it will give their employees the skills needed to find other opportunities with potential competitors. Investing in training for your existing talent will have the opposite effect. When your talent sees you invest in them, it will increase their loyalty to you and ultimately improve your employee retention.   

Additionally, the same survey noted that many businesses wouldn't need to make as many hires if they upskilled their existing employees. With the rising financial costs of hiring new talent, upskilling current talent is a more cost-effective option.

Get in touch with our data science recruiters

The increase of businesses needing meaningful analysis of an ever-increasing data pool means that demand for such skills will continue to rise. In today's rapidly changing economy, companies must adopt and adapt different recruitment strategies to meet this challenge head-on.

A successful approach will require a granular understanding of business needs to future-proof employment demand. Whether through AI, upskilling professionals with similar skill sets or retraining the workforce, companies must understand the underlying mechanisms to help companies optimise decisions.

As experts in the technology recruitment industry, we recognise why data science talent is hard to find. Thankfully, we also know how to source hard-to-find talent within the market and secure top professionals with the transferable skills needed to meet your data science recruitment needs. If you need to fill your data scientist jobs with specialist talent, we can help. Get in touch with our data science and technology specialists today and progress your business with Amoria Bond.