Hiring Trends in Predictive Analytics for 2018


by Alex White

Senior Partner, Talent & Research 7th Jan 2017

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Alex White is the founding partner at Avellio. He is an industry experienced former analyst, and has led over 120 retained search assignments for data science leaders, with mandates entrusted by leading global investment banks, major retailers and analytics consultancies.


This is an edited version of our forthcoming report: ‘Compensation & Predictive Analytics’, a forecast for 2018. The full report due for publication in June 2018 will provide insight gained from our biannual client survey, and will deliver trends and opinion on compensation for predictive analytics professionals across all key industries.

The role that predicative analytics plays in business is growing ever larger and more important every year, and shows no signs of slowing down. The rapid rise of Big Data in enterprise, and the increasing interrelation between data science and predictive analytics is fast becoming more prevalent for commercial organisations. In this short report we take a closer look at several of the new advents in the recruiting space, and what this means for both hiring companies and predictive analytics professionals. 

‘Quants are on the move’

We have been tracking and compiling data for over 3 years on predictive analysts job movements. Our research tells us that traditionally 47% of predictive analysts have been engaged within the Financial Services and Marketing sectors, where the demand for coverage on aspects such as credit risk and consumer insight has seen the greatest demand for talent.  

But this is all starting to change, with use cases for analytics becoming a priority and demanding a greater share of marketing budgets across wider, alternative industries. In particular, our data for 2017 suggests that Financial Services and Marketing saw a decline in actively engaged analytics professionals to 42%, and a significant segway of PA talent in to new industry sectors that are visibly making a greater commitment to long term investment in analytics, notably in areas such as technology, healthcare and insurance.

Broadly, for any company or organisation looking to hire an experienced PA this poses a significant challenge, with the diversification of analytics across industries, it therefore becomes essential to exercise some flexibility in the hiring brief, broadening the scope to include analysts with indirect domain experience is a necessary measure to widen the talent pool. Generally, Hiring Managers accept that analytics skills are transferable.

‘Data Science and Predictive Analytics roles are becoming a blend’ 

The work of Predictive Analysts is gradually evolving and becoming even more high level. Many embrace continuous learning and have begun to learn to utilise many of the tools and methodologies that traditionally only Data Scientists have employed in the past. No longer are Analysts bound to SAS, today’s Analysts are now adopting R and Python as the new statistical tools of choice. This serves a duality of purpose, as it increases an Analysts marketability in the labour market, whilst also posing a fresh challenge on the job to learn and command the use of next level tools to enable improved data management and to gain greater insights. 

Predictive Analytics leads to insight, and action, creating greater commercial value

Companies that achieve the greatest returns from data teams are the ones that truly understand that they get bigger gains from predictive analysts when they actively translate analysis in to insight, and then go on to recommend actions, rather than simply being left to developing models. Business leaders want to know what the analysis and insight means for the business, and what the next action should be. The key to effective communication is for Analysts to learn to explain concepts in simple, yet effective terms that create impact, resulting in improved collaboration, greater trust, shared vision and goals. 

Data leaders need to influence stakeholders and fly the flag for the Analytics team

The data team leader must be a succinct influencer as well as a strategic leader. They must communicate the value enterprise-wide that their team provides, whilst developing partnerships with other senior leaders in the business, as executing analysis is not enough when establishing the analytics team’s value alone.

There has never been a better time to become involved with Analytics

Opportunities are continuing to multiply for companies and professionals alike, and year-on-year the hiring market for predictive analysts has remained very robust. We expect even greater competition for Analytics talent in 2018, which is good news for progressive companies and ambitious career Analysts.


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By Alex White
Alex White