Have you ever interviewed for that “Ideal Job” only to fall at the first hurdle? Or had an interview and felt that you were a racing certainty only to be turned down for reasons you could not quite understand?
Most of us have been interviewed and rejected for a job we wanted. Understanding the pitfalls that are particular to analytics-centric interviewing can help job applicants ensure success.
The following is a rough guide to preparing for analytics job interviews.
In our experience, the most common reasons for rejection of candidates after interview are “lack of commercial thinking”, “inability to articulate results” and, believe it or not, being “purely delivery focussed”. Looking at feedback across a diverse employer base, the following observations emerge.
Lack of commercial thinking
The ability to build or utilise a statistical model is a well-regarded skill within an academic environment, but the growing demand for decision-able output means that it is only half the story. Analysts who only answer the “what?” need to start thinking about the “why?” and the “how can that information impact on the bottom line?”
- Preparation is key – bullet point 1-2 specific pieces of work for which you have been responsible.Ensure those examples enable you to talk about a result, link your work to a commercial implication rather than analytics for analytics sake.
- Utilise examples where you are making recommendations or providing insight in order to facilitate a business benefit.
Ideally, you should talk measurability, talk ROI. Talk numbers! What was the change you effected with your analysis & recommendation? A percentage increase in customer take-up for example? A reduction in cost? A measurable increase in profitability?
Be realistic about what you have affected – exaggerated results are easily spotted and challenged
As businesses’ analytics functions mature, it is becoming increasingly common for analysts to be proactive in spotting opportunities for extra commercial impact; inability to demonstrate an aptitude for this is a frequently-expressed reason for rejection at interview.
- Think about examples you can give where you have seen an opportunity/issue that has allowed you to utilise analytics to effect a result. Even if you don’t do this as a major part of your role, you need to demonstrate the capability and desire to do it – is there an opportunity for you to do it in your current role? Try! Having tried is better than not even considering it. And remember: the collateral effects of your work elsewhere in the business could be positive or negative, so embrace and understand that bigger picture.
In summary, analytics interviewing relates in the main, to the skill of applying numerical thinking in a logical, consistent manner to commercial problems; preparation around impactful examples with linked quantifiable results and identification of additional insight and opportunities can drastically improve your chances of getting that dream role.