In an attempt for companies to gain greater value from their data, we are collecting more and more data than ever before. As a result of this, the role of the Data Scientist is becoming highly sought after. A recent report released by Glassdoor, predicts that the role of a Data Scientist will be among the 25 highest paying jobs in 2016.
Here at ROD, we have always predicted big things for big data. Back in 2014, Resource On Demand’s CEO, Lee Durrant, commented on what he predicted for the future of Data Scientists. He had this to say “Technology is a vital tool in the Data Scientist toolkit. It enables them to manage vast volumes of data and get data ready for analysis at a much quicker rate, than ever before. We are expecting to see a real proactive future taking shape for Data Scientists in general”.
What is a Data Scientist and what do they do?
A Data Scientist is a trained professional, responsible for managing and analysing large, and often complex data. This data is then used to create tools which can be used within businesses to gain competitive advantage and market / product knowledge.
These types of roles are perfect for those who are data-driven problem solvers. Having a strong technical background will align you on the pathway to becoming a successful Data Scientist.
What skills are required?
Data Scientists have knowledge of both data handling and data mining processes. In addition, you are likely to have a strong mathematical / statistical background, and perhaps a degree in Computer Science. You should also possess some programming experience or skills within the following:
- Programming languages (i.e. R or Python)
- Database querying language (i.e. SQL)
- Big Data
- Data virtualisation
Great communication skills are also essential and the ability to explain complex analysis to non-technical people.
How do I become a Data Scientist?
There are various ways in which you can become a Data Scientist, but gaining experience working with real data is going to be key. If you do not currently have experience in the above areas, you can look for specialised programming and statistic courses. Or, you could also look for the following opportunities to gain experience:
- Signing up to hackathons
- Helping out at a local startup company, dealing with data issues
Read more of our articles on Data Science here.