Good evening all,
It has been a few months since I last posted here. I am based in London where I have spent most of my career as either a web developer or a web analytics practitioner. I have now over 6 years' experience in database, server-side and front-end development but more recently, an additional 10 years in web analytics, mostly on the implementation side of things. Over the past year or so I began reading articles about the emerging role of Chief Data Officer with great interest. In May this year, I met Peter Jackson, not the filmmaker but the CDO at local water utility company near London as both of us presented at the Data Festival London. Peter was about to start a free online course to explain to us with another fellow CDO what the role means, how according to Gartner the companies will start needing CDOs en masse from next year onwards. Peter Jackson and Caroline Carruthers were the teachers and based the course on the book they co-wrote, The CDO Playbook, which has great reviews and which I also recommend. I am proud to say that I have completed that course as a student of the very first class of the Chief Data Officer School. But I am none the wiser about the what the career path toward becoming a CDO could be like. Well, almost...
I was the only web analytics practitioner in that class. Peter and Caroline considered that people like me can become a CDO but it would be much harder than people with different data backgrounds. More recently, I was checking the website of a UK-based recruiter specialised in Analytics called Harnham. I spotted a new blogging section on their website and CDO, Noam Zeigerson, was sharing his thoughts there. Now Harnham does not recruit CDOs so I was rather intrigued to see a CDO posting there so I reached out to Noam and asked him for his thoughts about what this elusive career path could look like. Although Noam did not have any clear answers, he did suggest that web analytics is seen as different to any other kind of data-related career. First, the type of data we handle is different from any other kind of data the organisations generate or acquire. Second, the kind of tools we use to analyse web analytics data are limited to web analytics data and do not let us analyse any other kind of data.
One possible career path might be becoming a Head of Analytics first. I lead a discussion at MeasureCamp Brussels last October. I did very basic research ahead of the discussion by looking at the LinkedIn profiles of several Head of Analytics. I was only able to look at 20 profiles before LinkedIn blocked me from viewing more profiles so my sample is tiny to be sure. But it suggested that only 3 in 20 Head of Analytics had any prior web analytics experience. The most typical profile was someone with a Masters in either Statistics, Maths, Economics or an MBA with some kind of data science experience. I guess it makes sense. The rare few Head of Analytics with a web analytics background suggest that the role title combines really two very different roles and the web analytics flavoured Head of Analytics seems to be the rarer of the two. This suggests that, at least from where I sit which is the United Kingdom, there are very opportunities to move ahead in web analytics and other data careers once you had 10 years' experience in the field. Many of us here are becoming contractors in our quest to earn a bigger paycheck as a result.
Another possible path might come from leveraging our favourite web analytics tools' APIs along with R and Python. At this stage, we only use the web analytics web interface when it is expedient. Most of the time, we extract the web analytics data, clean this data, combine it with other data sources. After all, I am used to seeing more and more presentations at MeasureCamp in Europe about R, Machine Learning with TensorFlow, Markov Chains-driven attribution modelling, Sentiment Analysis, Kubernetes and Docker. At this point, it seems to me the typical user of our web analytics web interfaces is less and less a web analyst but more and more one of your organisations' colleagues from all other teams. Perhaps we are beginning to see a convergence of the two types of Head of Analytics and even the emergence of a hybrid of both types. These hybrid Head of Analytics might have one foot in the web analytics realm and another one in the pure data science realm.
Web analytics data is certainly a lot messier than any other type of data that organisations see. It is rarely normally distributed, you only get if the customers gave their consent and if they support Javascript and cookies. I believe that these hybrid data-scientists are more likely to come from the ranks of web analysts experimenting with R and Python than from data scientists wondering what is web analytics is all about. After all, their lack of exposure to web analytics does not seem to limit their chances to become a Head of Analytics as I explained above. With greater visibility, the hybrid data scientist might appear as a stronger choice for organisations looking for a Head of Analytics and even more senior roles. As a web analytics implementation expert, perhaps I should learn R and Python, a few sophisticated approaches in these languages to analyse data from other sources than web analytics and pursue more data science roles such as Associate Data Architect and eventually a CDO perhaps. Please let me your thoughts. How is it like over the pond? What are the typical career paths of people with 10 years' experience in web analytics? Can web analytics people have a better chance senior data roles such as CDOs?
Alban
@albangerome
#CareerAdvice