Big Data, Small Data, Predictive Data – What Data Jobs are Needed Today? | Empiric Recruitment
Data roles are changing
Increasing numbers of organisations in every sector are seeking the expertise of big data specialists. The current demand for data specialists significantly outstrips the supply.
However, there is a fundamental shift taking place in how businesses look at data roles.
“The trend that a lot of people have been talking about is the shift away from the title of data scientist,” says Mark Stevenson, Empiric’s Data Manager. “It had this unicorn status of describing a polymath, who’s able to build machine learning algorithms but is also able to communicate effectively and to use advanced stats. What companies actually need from a data scientist, though, is a lot of data engineering – because they need to be able to build and draw out a lot of this data, not just be able to run models on it. Because of that, there’s a trend towards getting more data engineers out there, where being more robust and techie is even better than being an analyst. Because of that, we’re seeing a return to the traditional dichotomy of analysts and engineers.”
At the same time there are increased expectations being put on the shoulders of these individuals. “One of the developments I’ve seen is the hybridisation of job specs and skillsets,” says Mark. “What businesses are looking for now isn’t necessarily traditional analytics, business intelligence or web analytics, but a bit of all of it. They want an analyst who’s able to visualise some of their reports, using open source visualisation tools like Tableau. In the past that would have been a more traditional BI role, but because you’re using open source tech, the individual needs to have experience of the Big Data stack as well as BI skills, like Microsoft’s SQL. Equally, data scientists are being asked to have visualisation skills and Big Data guys are being asked to have traditional programming skills.”
Market driving demand for data
AI is among the most fertile fields for data. Where Big Data is used in supply chain management, the inspection of industrial processes or the provision of market analysis and forecasts, AI has the potential to assist, parsing information, automating analysis and rapidly providing actionable insights and predictions – without humans necessarily needing to touch the data itself. “One of the biggest applications of Big Data is in various implementations of AI,” says Mark. “There are lots of AI start-ups and AI businesses that are selling machine learning solutions to everyone from companies in the corporate sector to the civil service. There’s a lot of investment from UK businesses into artificial intelligence, in fields from self-driving cars and robotics to ecommerce and the supply chain – and even in things like drones, which might soon be delivering your UberEats.”
GDPR, coming into force on 25th May, will pose challenges for the use of Big Data, however. Being able to provide individual customer data and to remove it on request will require navigation of both the legislative requirements and the database – and it will be imperative that removing individual data entries does not compromise the integrity or the utility of the whole. As well as mandating increased controls on the processing and collection of data, the regulation also requires a named individual to be responsible for the company’s data use – a provision that will have many organisations hiring a Chief Data Officer, with board level responsibility, for the first time.
“Looking ahead, there’s more acceptance that you have to be looking for individuals like Chief Data Officers and they need to have more power within the business,” says Mark. “Companies need to drive that agenda for their data platforms and it needs to come from someone at C-level.”
More regulation may also be on the way, though. “Facebook might undergo quite a lot of scrutiny over its data regulation rules and that’s going to see a big shift,” notes Mark. “I imagine data science and the use of sentiment analysis are going to be up front and centre in the debates over the next year or so.”
Businesses are increasingly pursuing a cloud-first strategy for Big Data analytics – and it is expected that more than 50% of Big Data workloads will take place in the cloud by 2019.
Graduates with deep learning and machine learning skills are in high demand but courses like S2DS and ASI are particularly useful in helping PhD students to secure roles in data science and AI. Attending conferences, events and meetups is also a highly effective way of staying abreast of trends and developments in the field – as well as being an opportunity to meet experts and to find jobs. “There’s a huge meetup fraternity and everyone does try and help people,” notes Mark, who also runs the ‘Data! Data! Data!’ Meetup group.
Executives in all fields are advised to develop the skills needed to manipulate and to develop insights from data – and there are an increasing number of tools available that enable non-specialists to interact with large datasets and to gain meaningful insights from them.
At the macro scale, there’s little question that the future is bright for data. As Mark notes, “Data sits across everything.” While analytics and forecasting have become increasingly important for businesses over the last two decades, the effective deployment of data will become integral across all industries and at every level in the years to come. As Forrester notes, “All companies are data businesses now.”
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Empiric is a multi-award winning business and one of the fastest growing technology and transformation recruitment agency's specialising in data, digital, cloud and security. We supply technology and change recruitment services to businesses looking for both contract and permanent professionals.
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