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.”

Skills

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.”