Data Market Observations: March 2023

After spending some time discussing current trends and issues in the current domains of data and technology, the feedback we are receiving is that many data leaders are observing some interesting trends that we want to share in this month’s market piece.

Data science remains one of the most in-demand and rapidly growing fields and with its increasing popularity, the job market is becoming more competitive. For new talent attraction, many data science candidates are looking for supportive mentorship and educational opportunities from their employers and data leaders are reporting this to be their focus in  stablishing enhanced employment propositions to support the growth of their teams.

Beyond this, candidates want to know that it’s not a one-time activity and that for existing talent and teams, businesses must continue their focus on upskilling their data workforce to meet the demands of ever evolving data-centric business models.

For those who consider they are getting it right, such upskilling of their existing talent is being achieved through partnerships with educational institutions, training programs, and upskilling from within. For instance, Salesforce recently launched a free online learning platform called Trailhead that enables aspiring tech professionals to earn CV-building certifications and tech skills.

Our 'ring-around' this month has also surfaced that companies are searching for data science
specialists with niche skill sets such as deep learning engineers, NLP engineers, computer vision engineers, risk data scientists, machine learning engineers, data engineers, and machine learning operations engineers. This trend has made it more challenging for data
science generalists to grow in the field.

Many data leaders we spoke to indicated that their companies expect data science specialists to quickly apply their existing skills to solve specific and sometimes singular problems the company is facing, so here, some additional domain knowledge to accompany deep technical skills is the order of the day (and in high demand!).

Finding the best talent remains a challenging activity but once located, attracting the best
becomes the next hurdle. We’ve observed that candidates are looking for a strong company mission that aligns with their personal interests and values. Data scientists are often motivated by topics such as ethics and sustainability and companies can set themselves apart by being involved in such initiatives.

Data science is not limited to large listed businesses and companies of all sizes, locations, and industrial backgrounds are hiring for data science talent across the board and this is putting more pressure on the marketplace as the best talent do not necessarily gravitate towards the largest ventures!

Instead, they favour companies that can offer supportive mentorship, niche skill sets, and a strong company purpose so putting this front and centre appears to be the order of the day. Project wise, some of the anecdotal feedback coming from data leaders relates to the organisations themselves. Many companies know they want and need data science talent for a variety of company projects, but several are putting pressure on their data leaders to hire for these roles before they realise the exact scope of their projects!

In our experience, when businesses move forward with disorganised data goals, they find that data science professionals become frustrated and quickly move toward new opportunities. Data leaders have signalled to us that this dilutes the prospect of enhanced retention and massively harms their employment proposition.

Finally for this month, additional pressures caused by the current economic climate are making life tougher for our community of data leaders. Challenges beyond their data teams include funding, and preparedness to incorporate data talent into flat business team structures. This in turn is creating an issue with centralised support which data executives believe stands in their way to outperforming competitors with data science. To build a winning data analytics offence, CDOs and CDAOs believe that their organisation must modernise their internal team structures and elevate the roles of CDO and CDAO.

Will this change in the next year? What are your views?

What to know more?  Drop us a line here.

Author Bio


Michael started MBN to deal with what he perceived as a weakness within the recruitment industry and its lack of deep domain expertise in the areas of data, analytics and technology. 15 years on, MBN is a hugely successful and market leading provider of People Solutions to disruptive and fast moving businesses seeking the very best talent to support their strategic intent. MBN’s success has come about through leadership and passion to collaborate and build communities of stakeholders. In recent years this has been evidenced through organising and facilitating two of the UK’s most compelling networking groups: Scotland Data Science & Technology and Blockchain Scotland Meet-Up Group. With such groups playing a pivotal role in helping to surface unmet clients’ needs and helping to build links with an enhanced candidate pool, he has also used this as a platform for growth by hosting events such as ScotChain, CityChain and Data Talent 2.0. Outside of MBN, he continues to act as an advisor and mentor to a number of start-ups, charities and third-sector organisations and have provided support to many government agencies seeking to understand the evolving complex landscape of Data Talent Acquisition.