As we have a growing number of proteges who work in data and analytics roles, including quants, actuaries, engineers and others, this post explores some of the types of roles which exist in data science and analytics. Given the speed at which the analytics landscape and the technology used are evolving, it changes significantly over time, so please don’t treat these example roles as static or exhaustive. In fact, this ongoing evolution is one of the exciting aspects of such work: the opportunity to spot gaps and propose innovative ways to do things in future, including crafting your own role and career path.
More senior data and analytics professionals may also appreciate our long Routes to the Top article on C-suite roles like Chief Data Officer, Chief Analytics Officer and Chief Data & Analytics Officer.
Data and analytics roles have to some extent exploded because of the rapid evolution of technology, although they also incorporate strong statistics skills, and some feel that domain knowledge of an industry or industries is also helpful. With this in mind, here are some examples of roles:
Data Scientists or Data Analysts
Some of these roles might be done by the same person. There are also other related roles beyond these, such as experts in visualisation i.e. telling graphical stories with the data so that it supports the decisions being recommended.
We end with memorable day-at-the-beach descriptions of three data roles, courtesy of Stonefield Advisory, a UK-based data analysis & financial modelling company: