Growing the data science team isn’t as easy as you’d think.
– a quick internet search shows not only that data science is the sexiest job of the 21st Century but also the breadth of job descriptions that fall under the title. It’s no wonder those wanting to enter the profession and those seeking to hire get confused about what skills are needed.
The nub of the problem is the wide-ranging tasks data scientists work on, and that is certainly very true here at Bays. Whilst we focus on two core areas of predictive modelling and statistical analysis, what that means, in reality, is that the projects we work ranges from making recommendations on experimental designs; setting and testing hypotheses; defining and measuring metrics; spotting and tracking trends as well as building mathematical models.
Building a really strong data science team needs a diverse set of talent all of whom have the right to call themselves data scientists. So what is it that unites the teams? There are, I believe a few skills which are their ability to:
- Understand and interpret the questions that our clients are asking
- Bring their passion, enthusiasm, and enquiring mind to work
- Care about making an impact
If data scientists can bring this to work, then it falls to me as the owner to make sure that those who work for Bays get to work on exciting problems, which challenge and stretch our team members to learn new skills; deliver their best work and see where they are making a difference. Our analytics work helps our clients to see the story within their data and ultimately drive forwards on their business decisions. The statistical analysis aspect of our work gives a clear overview of the impact of change and provides evidence to support decision-makers whilst the development of predictive algorithms lets us work with the latest coding and mathematical advances to create novel solutions.
Building a data science team isn’t about whether we need to use R or Python (or any other coding language for that matter), it is about developing a curious mindset, allowing employees to have thinking time to investigate new approaches and bringing in diversity of thought. It’s a lot of fun watching our team grow and seeing how people, when allowed, bring so many skills to each of the projects we work on. I’m excited to meet even more data scientists in the near future who have very different skill sets to me and the current data science team at Bays.