More and more companies are becoming data driven in order to help them make better business decisions. The rise of this niche over recent years has caused an increased demand for those who can collect, organize, and analyse data. If you’ve hired for this position in the past, you should know this isn’t an easy task.
As I have been through this challenging process several times, I thought I’d summarize a couple of key lessons I learnt a long the way. For me the top lessons learnt are:
- Defining a Data Scientist – One way to subdivide data science is:
- Business Intelligence – The key is to make the right data available to the right stakeholders, in the right form. You require someone with good data analytics and data visualization skills.
- Decision support – to help businesses make informed regular or ad hoc decisions. You need someone with data analytics, data visualization and predictive modelling skills. Optimization/OR experience is also often valuable here.
- Deployable machine learning – A fair degree of computer science and software engineering skills are going to be required.
- Abandon ‘whiteboarding’ – It is common practice to request a candidate write in front of the interview panel a piece of coding (on either a whiteboard or a screen). This on-the-spot method can put the candidate under too much stress, which eclipses their true abilities. Also, the challenge and the environment is not reflective of real life situations. An alternative to this would be provide a data science assignment which can be completed at home in their own time. This way the candidate has time and peace of mind to deploy their abilities to the full. The candidate can then return and present the result to the interviewers and Thus, the candidate’s real communication skills can be assessed.
- Experience – It can be tough to recruit a Data Scientist at the best of times, let alone candidates with specific commercial experience. This is true particularly in Cambridge as the majority of candidates come from an academia/research background. The salary difference between someone from academia compared to that of somebody with commercial experience can be doubled. So, if your company has the time and resources to invest in up and coming talent looking to enter the commercial world, a huge saving can be made.
- Relocators – With demand high and supplies low, it is likely the ideal candidate will be a relocator from within Europe. It is definitely worth reviewing relocation packages to ensure you are competitive with local competitors.