Salary Surveys: Are you being paid fairly?

Salary surveys always tend to gain participants. Most people are interested in finding out how much others are earning or whether they can make a case to be paid more.

All too often one hears  of analysts leaving one company, where they were told a pay rise could not be justified, to then see a job ad for their replacement advertised with the higher salary requested (or higher).

It isn’t easy for employers either, of course. As we’ve mentioned before, people like data scientists, analysts and the rounded insight professionals (who combine technical skills with the softer skills needed to make an impact) are hard to find. So, the laws of supply & demand tend to drive up salaries.

But it is still more cost-effective, for most businesses, to retain & pay more to incumbents who are delivering than need to incur the costs of hiring again. So, how do insight professionals & their bosses judge what is a fair salary? Few businesses have separate pay scales or ‘job families‘ for insight roles. That would be a good place to start.

To help with that, more & more salary surveys and benchmarking are being published – especially in the US. A couple caught my eye this week.

First, Quirks Magazine (always worth reading for research professionals), published the results of their latest market research salaries survey. This is US-based, but given the European job market tends to follow the US, worth reading:

A couple of things struck me as interesting here. As you’d expect, the more senior roles (C-Suite, directors, VPs et al) are paid more. But below that there are some interesting differences. If you look at the research job titles within Corporates, rather than Agencies, amongst the lowest paid jobs are research assistants & even research analysts. However, statisticians are paid considerably more, sometimes even more than the managers of research teams.

Interestingly, on the agency side this differential is reduced and the roles paid considerably more than they are on the client side are more sales & relationship management roles. Perhaps statisticians in agency research teams should seriously think of moving to client side roles, with researchers in corporates considering a stint in an agency?

An interesting comparison to this view of how much researchers are paid is a recent analysis (also in the US) by Frank Lo who is the Data Science Director for Wayfair. He has used his own experience, plus published salary survey results and data from recruitment agencies to recommend salary ranges for ‘big data roles’. Despite the ambiguity of that term, his post is an interesting read:

Although I might disagree with some of his description of ‘data scientist‘ role as the natural progression from data analyst (without having marketing or customer insight analyst roles), his comparisons are interesting. Once again, as you’d expect, there are higher salaries for more experience & seniority (from data analysts up to data scientists & data science/analytics managers).

Here Frank’s use of salary ranges is insightful. One sees a similar pattern to the valuing of statisticians in client-side research teams, but even more so. The ranges show that an expert data scientist could earn as much or more than the manager of that team. Appropriate in response to market rates but tough for most corporate cultures to accept.

Beyond those roles, it is then also informative to see how two more specialist data/IT roles are positioned in terms of pay. Sadly DBAs appear to be suffering from an image problem (probably that more IT sounding title), as they are not paid as much as data scientists. Perhaps this is another reflection of the undervaluing of the importance of data modelling & design – as is becoming apparent in the results of our survey.

With a change of job title to ‘Big Data Engineer‘ though (and no doubt some cramming on Hadoop, NoSQL etc), such a data centric IT role can match or even exceed data scientist salaries. This, to me, reveals the dirty little secret of the current fashion for Big Data & Data Scientist roles. Under the skin, a lot of what is being touted is actually more IT investment & the continuing struggle to improve data infrastructures (now that CRM investments are unfashionable). If organisations are not careful you are really paying another type of IT spend here, not truly investing in understanding your customers better.

Anyway, I’ll step down from my soapbox for now. I hope that information was useful. Do you see the same differentials in salary for different types of insight role in your business? If you are an insight leader, how do you ensure you’re paying a fair salary for the technical expertise you require?