Written by:
Alex Liggatt

How to future-proof
your Data Science

Data. It’s big business these days.

To be more specific, there are 2.5 quintillion (that’s 18 zeros) bytes of data created every single day. And companies are desperate for clever folk who can convert this data into valuable insights to help their businesses succeed.

This means that being a master of data can be a lucrative career choice, not to mention a rewarding one. Even the government says that unlocking data across the economy is vital in helping ‘propel the UK forward in the recovery from the coronavirus pandemic’. Hence it’s set out a new strategy to kickstart a ‘data revolution’.

Yet, just like other jobs, certain roles, skills and knowledge in the field of data are more sought-after than others – and knowing what they are is key to future-proofing your career. So, without further ado…

What data roles are in demand?

Here at Revoco, we’re seeing a high demand for data engineers and data scientists. With most roles concentrated in the London area, we’re helping our candidates secure salaries of around £80-£120k, and day rates from £500-£750.

What skills are most needed now – and in the future?

If you’re already in data, you may already be adept at things like programming (if not in Python, then make sure it’s on your to-learn list), probability and statistics. But where else should you be looking to expand your knowledge and expertise?

Machine learning (ML). A key skill for large and/or data-driven organizations. As Towards Data Science notes, ML for data science includes algorithms that are key to ML, like K-nearest neighbours, Naive Bayes and Random Forests.
Natural language processing (NLP). A skill that’s at the top of many hiring managers’ wish lists, especially in financial services and healthcare.
Data visualisation. Specifically, using Tableau (sorry ExCel), which is predicted to lead the market in coming years.
Data wrangling. Data’s a messy business. Companies are actively on the lookout for pros who can cleanse data of its imperfections, restructure and enrich it.
Cloud. Most organizations have moved their database to AWS/Azure, says R-bloggers, while many others are implementing cloud-based production models. That’s why it pays to master the basics of Docker, containers and deploying code and models to the cloud.

Certification and courses

In terms of certification, Microsoft-based courses should be your first port of call. Microsoft Certified Azure Data Scientist Associate proves your ability to define and prepare Azure development environments, prepare data for modelling, and more besides. You can access free online training or a paid-for course, with the exam costing $165 (around £128).

For the same price you can study and take an exam for the Data Analyst Association certificate, which will prove your subject matter expertise in helping companies leverage data assets using Microsoft Power BI.

When it comes to other courses, check out this handy list of the top seven online data science courses this year.

What about other skills and attributes?

The idea that data pros are siloed in a company and hide behind their computer screens is outdated and just plain wrong. Today, data touches every part of an organisation, which is why soft skills like stakeholder, people and project management, and communication overall, are more important than ever. Have these attributes in your arsenal and you’re onto a winner.

Two more things…

It doesn’t hurt to regularly cast your eye over data science blogs to keep abreast of current and future data trends.

Also, we strongly recommend forming a great bond with a specialist data scientist recruitment consultant who knows your niche and will be able to update you on market shifts when it comes to employability and in-demand skills. Which is where Revoco comes in – get in touch with our Data practice to take the next steps in your Data Science career.


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