Analysts & Data Scientists, How to Choose Your Next Role (Part 2 of 4)

Part One | Part Two | Part Three | Part Four

Welcome to Part Two in our four-part series on choosing your next data science or analytics role. In Part One, we looked at the question of role Location & Timing. While these can be the biggest deal breakers, this time around we consider two other important aspects: Industry & Organisation.

Usually you will be working in one particular industry, such as automotive, fast-moving consumer goods, or luxury goods. However, in roles such as technology sales or consulting you might have the opportunity to work across multiple industries. Which of these is more appealing to you? Your appetite for broad professional experiences should help you decide what the right path is.

It is important to acknowledge that your level of personal interest will have a huge impact on your job satisfaction. If you are passionate about an industry, it is far easier to remain motivated in your work as time goes on. Familiarity with a particular industry can also be major advantage, as you develop domain expertise that others will find hard to match.  As data science is about making better decisions with data, understanding a domain will also help you know which decisions are worth making in the first place.

Consider that not every industry has the same level of maturity in data, analytics, and AI. In the tech industry data science is highly prevalent across every domain, which means that you are more likely to get exposure to cutting edge platforms and algorithms. Conversely, in many traditional industries such as agriculture, retail, and finance, there is often a lack of maturity in advanced analytics and data science. This does mean that you can potentially have more of an opportunity to own and drive analytical change in the organisation.

We should also raise the topic of regulatory environments. For examples, finance and healthcare in particular are highly regulated industries where the capture and use of data is heavily restricted. This can affect your ability to utilise certain tools and techniques, so it is something worth thinking about.  It can also have a significant impact on the rate at which new innovations such as AI are adopted. Having said that, innovation can come from anywhere so it does help to keep an open mind while interviewing.

Next, what company are you considering? What role do they play in the industry? Are they a respected veteran or a scrappy disruptor? Are they a specialist or do they have a broad range of operations? Are they growing their business or not? Do they have a strong presence in terms of data, analytics, and AI? All of these factors will affect your opportunities and should be weighed up. Make sure to look past the shiny exterior and take the time to understand what the organisation is like. It helps to prepare questions to ask in your interview.

The most critical factor in this category is the company culture. Whether it is a progressive company that provides its employees with flexibility and autonomy, or a traditionally hierarchical organisation, make sure it works for you. Does the culture align with your own workplace preferences, philosophies, and values? Never underestimate the importance of this. No amount of money will make you happy if you hate the culture. One good way to understand what it might be like working for the organisation is to check out the reviews on Glassdoor, although beware of biases!

You should also be aware of the reputation of the organisation you are considering. Are they seen as an ethical player in the industry? Are they highly regarded – or not? Closely related to this is the question of the organisation's mission. Can people both inside and outside of the organisation relate to this? Not only can this be a major motivator during your career, but having a clear mission can also help you both scope and afterwards promote your analytics and data science work more effectively.

Focus, passion, maturity, regulation, scale, culture, reputation... many factors to take into account when reflecting on your choice of Industry & Organisation. Next week in Part Three we will look at the topics of Manager & Team. If you have questions or comments, please drop us a line on LinkedIn!

– Ryan & Colm