While actuarial work is not confined exclusively to the banking, financial services and insurance (BFSI) sectors, data science skills open opportunities for actuaries to boost their professional value and move their careers into other businesses and industries.
Many verticals show a demand for data science skills. Online recruiter Indeed sees a 30% increase in demand for data scientists year-on-year. But searches by data science job seekers grew at just 14% – which suggests a quantifiable supply-and-demand gap.
Three employment sectors that perhaps offer clear contrasts to finance are healthcare, automotive, and telecommunications.
Like the BFSI sector, healthcare is being disrupted by technologies driven by massive data sets being generated by diagnostic and treatment tech.
Data collected by patient monitoring systems informs treatment and preventative care programmes. Analysis of heart rate and breathing patterns, for instance, can detect slight changes in health indicators and predict possible disorders. Wearable technology, which monitors patients’ ‘health indicators’ 24x7, can collect up to 2Tb of data per-patient per-day.
Machine Learning algorithms, meanwhile, can detect and track common ailments, like coronary or respiratory conditions. Deep learning is used to read imaging data (x-rays, scans), and analyse it to reduce rates of diagnostic failure. All these applications need data scientists to be involved in some capacity.
Big Data analytics
As IFoA member Lisa Balboa notes, hospitals are using data analytics to forecast the number of patients likely to arrive at their doors in the coming week. Hospital managers use these predictions to adjust staffing and other resources to ensure anticipated patient demand is met.
With access to some of the biggest data sets, telecommunications companies are big proponents of Big Data analytics. As Springpeople notes, data from customer behaviours like SMS usage, video choices, social media activity, and past purchase patterns, enables telcos to offer targeted products and services. On the operational side, data scientists can also help monitor network activity to address performance issues.
With data storage costs down, and increased computer processing power with inexpensive analytics software tools, data analyst jobs have become much easier in the telecom sector, reports researcher Mind Commerce.
Machine Learning enables automotive manufacturers to discover new business models, finesse product quality, and optimise manufacture. Artificial Intelligence and data mining techniques are core to innovation in CAD modelling and simulation, analysis of procurement and logistical information. Data science also plays an integral role in the detection and remediation of production defects.
Other industries now hiring data scientists include agriculture, education, energy, manufacturing, media, mining, retail and travel.
What data science qualifications do actuaries need?
Actuaries realise that they operate in a discipline that’s ideal for the adoption of data science techniques, as the profession equips itself for the 2020s.
However, it’s critical that emphasis on qualificational and certificational attainment – the foundation of the actuarial profession – extends to the attainment of competences in data science.
The addition of data science to their skillsets will prove advantageous to actuaries, both in terms of greater career mobility, and the consolidation of their market value as actuarial professionals.
The maintenance of professional competences has always been core to actuarial practice, and this commitment is validated by Continuing Professional Development (CPD) and Professional Skills Training (PST) schemes. Going forward, data science curricular will increasingly meet the requirements of actuarial CPD and PST.
In June 2019, IFoA President John Taylor announced that a certificate in data science will be made available to all members of the actuarial profession. They will be able to choose from a number of modules that cover data science disciplines – such as data visualisation, Artificial Intelligence and Machine Learning – and can pick and choose from them. These module will be announced before the launch of the certificate.
“From this, actuaries will get a much greater appreciation of the art of the possible in data science,” President Taylor explains. “It won’t make them data science practitioners per se, but it will enable those certified to work more closely with data scientists. And the certificate will also have a currency with employers in evidencing the additional learning that actuaries have undertaken.”
Actuarial science and data science share many characteristics, such as data analytics and predictive data modelling; and so the undertaking of study-based attainments in the data sciences means that actuaries will already be familiar with some of the knowledge-acquisition necessary to make data science study part of their CPD/PST programmes and career progression.
Course-based data science qualifications broadly divide into those provided by professional associations (such as the IFoA and its partners), those from accredited academic bodies (like universities and academies), and those from vendors in the data science solutions market (notable examples are those from IBM, Dell, Microsoft and SAS).
The IFoA can help you find the courses to get you started. These courses are online, flexible, and sometimes cost-free. Each has value and provides a different perspective on data science in its many and evolving facets. You can also explore the options for an MSc, with several full- or part-time opportunities.
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