With increasing regularity, we read about one of the most in demand job roles in the 21st Century: Data Scientists. Whether in its purest form or even in the form of other closely related roles, the nature of such people and the skills they bring to modern business cannot be underestimated. They are pivotal to setting the new business agenda and helping to understand what the amorphous mass of data and information is telling us. So why is it that we still find organisations struggling to articulate what they really need from such talented individuals?
The starting point inevitably involves specifying the regularly illustrated skills relating to:
- Hands on technical skills with a number of tools and technologies, especially open source ones, such as Hadoop, Java, Python, C++, ECL, etc. Besides, having good understanding of database technologies, such as NoSQL database like HBase, CouchDB, etc.
- Understanding large-scale machine learning algorithms, programming and mathematical and statistical analysis. (Remember, you probably will struggle to recruit this generation of data scientists, you may have to build them. Academics that specialise in data analytics and research, such as econometricians are likely to be a good starting point).
- Strong business skills, including communication, planning, organising, and managing. A data scientist has to communicate with a diverse range of people in your business, that includes communicating and understanding business requirements, application requirements and interpret the patterns and relationships mined from data to people in marketing group, product development teams, and corporate executives. And all this requires good business and communication skills, to get the things done right.
- Good if not basic skills in data visualisation. They should be able to work with at least a few of the data visualization tools. Some of these include Flare, HighCharts, AmCharts, D3.js, Processing, Google Visualization API, and Raphael.js.
- An innovative approach to adding value. They should be able to see where data can add value, and how it can bring better results.
But is this enough?
We think one of the skills most frequently missing or at least the one most likely to be missed off the checklist is the ability to ‘Humanise’ the data. A recent Harvard blog discussed the point and made clear that ‘Data gives you the what, but humans know the why.’
The best business decisions come from a creative balance of gut, feel and insights informed by data. Using data in this way allows your business to build organisational knowledge and creativity on top of a solid foundation of data-driven insights.
In our experience this means more than interviewing candidates and more than just testing chemistry with those they will work with. To get it right such key staff and managers need to be given a ‘try out’. Simulating a real life case study pre populated with real, operational data might help but remember, the activity is intended to explore how they put the human touch to work around the data, analytics and the results to help you make sense of the information to hand.
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