The article, some of it using quite colourful language is really interesting as it explains some of the real challenges that Data Scientists find themselves in. The reality can be as Jonny (a Data Scientist) explains in his article, endemic and most of which as he explains really does make sense and sometimes difficult to stop happening.
Looking at it from the other side as a company that employs Data Scientists and other interesting species like Blockchain specialists our challenge is to ensure that what we agree to do with our clients, has a clear plan (outcomes are predefined and objectives realistic but also can be stretching) . We need to ensure that the teams of people we deploy on projects; typically a group with differing and complementary skills are maximising on using their skill sets, with the ideal, that as they do so they are also pushing the barriers of innovation to a new level and hence giving such individuals the fuel that makes them want to do more and achieve more.
Innovation is in our blood, with some of the first Big Data opensource banking projects going 'live' in Europe as early as 2010. First UK client bank (SIB bank) using Blockchain 'live' as part of their Banking services, out of the UK in H1 2018.
The barriers are sometimes where client changes mean that a new contact lead does not really have the same vision of their previous manager and hence sometimes a momentum on what started as a great project could end in a whimper. (Not a great outcome on the rare occasion such a situation happens).
Where this does happen, it is important that staff are moved to more engaging projects as much as possible however sometimes there can be 'in between' times.
Hence working in a major Consultancy like ours may give budding specialist like Data Scientists and Blockchain great opportunities and often can be a way of really cutting ones teeth. As a company we believe in continuous training, so down time can mean more training under ones belt and using the services of internal trainers; the everis University or self teaching.
At everis our most important asset as we started on day one over 21 years ago with 5 people were 'our staff'. Through organic growth our everis family has grown to over 21,000 Consultants globally and part of a global Consulting team which includes various other large established companies, to over 150,000 Consultants. We are in fact the 5th largest IT services group when added together.
Enjoy what Jonny has to say...
... and if you are interested in working within our group please contact one of my colleagues Kelly Woodgate one of the other contributors to everis Insights.
So if the project is taken on by an isolated data science team it is most likely to fail (or take a very long time because organizing isolated teams to work on collaborative project in large enterprises is not easy). So to be an effective data scientist in industry it doesn’t suffice just to do well in Kaggle competitions and complete some online courses. It (un)fortunately (depending on which way you look at it) involves understanding how hierarchies and politics works in business. Finding a company that is aligned with your critical path should be a key goal when searching for a data science job that will satisfy your needs.