Why Scale-ups Should Outsource Data Science

Marta Marino
Deeper Insights
Published in
3 min readMar 19, 2019

UK & US Data Scientists demand vs supply

Data Scientists demand is fueled by the increasing commercial adoption of Machine Learning and AI-powered solutions. In an article, Raconteur quotes a recent report from Accenture, forecasting that “ AI will add £654 billion to the UK economy by 2035. A significant portion of that will be outsourced to third-party service providers. Increasingly, organisations are looking at external parties to drive innovation”.

Data Scientists needed to slice through all the data and find insights, by building accurate prediction models, capturing patterns and anomalies in data that would normally take humans hundreds of years to process. For companies looking to accelerate their business, data and Data Scientists skills are invaluable, however, it is becoming increasingly difficult to source and find the right Data Science talent.

A January 2019 report from Indeed shows that in the US the demand for Data Scientists increases 29% year on year. On the other hand, Data Scientists’ supply grew at a slower pace of 14%, indicating a gap between supply and demand. An IBM report shared similar findings: they predict that the demand for Data Scientists in the US, will increase from 364,000 job openings to 2,720,000, by 2020.

This year, 80% of UK-based companies are planning to hire or seek Data Scientist Consultants. According to the EU Commission, 100,000 new data-related jobs will be created by 2020, however, there won’t be enough skilled people to fill the roles.

“Machine learning, big data and data science skills are the most challenging to recruit for, and can potentially create the greatest disruption if not filled.”

IBM’s The Quant Crunch report

With this growing gap between supply and demand for Data Scientists that makes it extremely competitive to hire, you add complication, and expense if building your own internal team especially at a time when you’ve recently raised growth capital and have product and revenue growth targets to meet. By outsourcing your Data Science requirements you’ll work with an efficient team that can hit the ground running; you’ll gain access to expertise and know-how that can build your cutting-edge technology, saving you time and internal resources. You’ll still retain ownership of the IP, but without the headache of developing it, while you can focus on delivering your business goals.

What are the benefits of outsourcing Data Science expertise?

Data Scientists aren’t just hard to find, they are generally hard to retain and training requires time, stopping you from reaching business-impacting results as quickly.

Outsourcing AI and Data Science solutions offer benefits including access to global talent pools, essential generalists skills and expertise that can solve business-specific problems with efficient model selection thus helping business leaders choose the appropriate technology to scale up rapidly. Businesses have the opportunity to leverage third parties’ larger volumes of data (i.e. unstructured web data), and to combine skills and technologies not yet available to them, with industry knowledge.

Data Experts are supporting businesses by picking the right models, data processing techniques and applying them correctly. Poorly thought-through AI applications can be highly disadvantageous by distracting a software engineering or IT team with data or systems requirements whilst not fully supporting a project and therefore setting it up to fail from the start. Working with an outsourced Data Science team gives space for internal development teams to continue on a day to day tasks while a longer Machine Learning project can be built and tested without distraction, to later integrate into the development teams roadmap.

Originally published at https://www.skimtechnologies.com on March 19, 2019.

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Marta Marino
Deeper Insights

Marketing Executive at Skim Technologies. Passionate about AI, tech for good and graphic arts.