Data Science

Discover actionable insights hidden in your data using advanced machine learning and AI algorithms. Most successful organisations are moving to data lead strategies where they rely on their data to provide evidence for hypothesis and direct business investment.

What is data science?

Data science is more than just a buzz word in the tech industry. Its purpose is to take the data that is collected by your organisation and ask the question what can this data tell me and how can it be used to improve an organisation?

This discovery process is guided by the scientific method where an hypothesis is made and then experiements are run to test the hypothesis. Data science combines more that just the scientific analysis of data. It also incorporates the prediction of future outcomes; like which customers are likely to respond to a campaign or forecasting the usage of a resource or service.

How it can help you?

Some examples of how data science can help include:

  1. Identify which marketing campaign is most relevant for each customer to generate leads
  2. Recommend products to customers based off purchase history and engagement to increase basket size/value
  3. Optimise your labour force for seasonal effects
  4. Tailor pricing to your customers needs using price experimentation

What to look for in a data scientist?

The best data scientists combine strong business acumen and industry knowledge with excellent technical and scientific skills. This combination of business and tech skills makes good data scientists as rare as hen's teeth. Our recommendation is to find someone who has a strong history of success in this space and knowledge of your industry.

Being a good data science involves deep knowledge of the scientific method, experience in how to apply the write algorithm and most importantly comprehensive knowledge of the industry and how the business operates. Without this last part the insights your data scientists come up with may not be actionable or relevant.