Welcome to the penultimate installment of our four-part series on choosing your next analytics or data science role. So far we examined Location & Timing in Part One, and Industry & Company in Part Two. In Part Three, we shift our focus to the people you will be working with closely, your Manager & Team.
The most important aspect of any role are the people you will work with. Of those people, your manager will usually have the greatest impact on your happiness and career progression. As they say, people do not leave jobs, they leave managers! Therefore it vital to get as much information about your potential manager as possible. Ask as many trusted sources as you can. Try to get a sense of their reputation as a manager and leader.
This can be subjective. Does their work style mesh well with your own? An authoritarian boss will not work for you if you are the type of person who values autonomy. Conversely, if you like clear guidance and a well defined scope, a hands-off manager will probably not give you what you need to develop. In some ways it is like entering a relationship; better to find a good match and grow together than to rush in and end up in an acrimonious divorce.
Beyond your manager's style and their values, how competent and well regarded are they within the area they work? Are they considered an expert in their field? Their work reputation will affect that of the team they lead, and therefore, you. While it might not seem fair, people have been shot down in performance calibrations because their manager was not seen as credible. Make sure that their reputation will open doors, not shut them.
It is also important to assess whether other leaders in the business will have control or influence over the work you will do. You want to avoid surprises later on, like finding out your project got killed because of someone you never even heard of! Understanding how much influence your manager has matters. A weak manager may not be able to stand up for you when you need them to. Make sure you understand how your manager’s manager fits into the picture.
Now on to the rest of the team; who are the people you will be working with on a day to day basis? Try to meet some of your potential colleagues in advance. Remember, the purpose of the interview process is in part to give you the opportunity to meet people. Do you get excited about the prospect of working with them? Are you going to be a specialist on this team – perhaps as the only data scientist – or are you joining a team of similar individuals?
While it can be intimidating to join a strong team, this is often the best way to learn. Usually it is far better to be a weaker performer on a strong team than to excel in a team of underperformers. After all, not only will you learn more in a strong team, but the team's reputation is very important too. Are they trusted in the organisation? Is the work they produce taken seriously? Joining a team with a poor reputation will make your job an uphill battle.
Finally, how diverse is the team you are joining? Being exposed to different perspectives will help you grow faster than working in a monoculture. It will likely be far more fun too. Think beyond the core elements of the role here. In many modern work environments, you will spend more time with these people than with your family or friends! Transactional work relationships are rarely fulfilling, so try to ensure you connect on a personal level as well.
The people you will work with determine so much: your ability to get things done, to learn, and to have fun. If the people you meet do not pass muster it is a major red flag. Do not underestimate the importance of people and culture. At the end of the day, an organisation is nothing but a bunch of people working together. In our final installment, we will look closer at your own role. Until then, if you have questions or comments, get in touch on LinkedIn!
– Colm & Ryan
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