It can feel like an impossible situation. You haven’t worked in a data role so you don’t have the experience and yet many organisations seem to be asking for experience. How on earth are you meant to get started?
What I see as a Data Analytics Coach is that people then end up heavily focusing on the technical skills to secure their first role. From online courses, bootcamps, and certifications to creating an array of projects to showcase their technical skills. Yet it can still be challenging to secure a role because organisations want to see application. Sure, you can create a data visualisation or write code. But do you understand what the business needs and how to communicate with stakeholders?
Getting started in a rapidly evolving industry
The data industry is still so young in many ways, but I’ve seen a massive revolution over the past 5 years where data functions are being called to account for what Return on Investment they are delivering. People cost money. And they need to show that investment is worth it. Having a highly technical team just isn’t enough to do that, they have to have the expertise to communicate with the business to help them deliver the right things at the right time.
And that takes experience. Hence the catch-22 situation that many people find themselves in as they start on their data career.
A radically different approach
I approach things in a radically different way which aims to get people focused on the right tasks at the right time. This helps them to secure the job that will give them that opportunity to gain the valuable experience. From here you can build and expand. Getting your foot in the door can be one of the biggest challenges in your career.
Focusing on the technical skills first can be a case of putting the cart before the horse. It’s useful when you want to explore whether it’s something that interests you, but after that you risk spending huge amounts of time going down a rabbit hole that might take a long time to come out of.
I recommend the Job First Strategy. This means the slightly unnerving task of looking for jobs first. Within it there are 3 phases.
Phase 1: Research
At this point you want to be thinking about the following questions:
· Where do you want to work?
· What is available for you in the region you are based? (Although in a post-covid world this might have expanded significantly compared to 3 years ago).
· What type of work interests you?
· Is there a particular industry you want to focus on that aligns with your interests and previous experience? This can be a great way in if you don’t have data experience but you are very knowledgeable about an industry and its processes.
Once you’ve done the research you will start to see what tools organisations are currently using. This is powerful because of there are no entry level roles using Python, guess what? Don’t learn Python (yet). Focus on learning the tools that will enable you to get your foot in the door. You can’t apply for jobs that require you to have 2 years’ experience of working in a data role if you’ve never worked in a data role.
Phase 2: Apply
Here you head into the even more scary apply phase. You literally have nothing to lose. Apply for entry level jobs, ensuring you have a stellar CV/resume as part of your submission. You want your CV to show that you understand what drives a business and that you can make an impact in what you do. That doesn’t necessarily have to include lots of data related activities.
Phase 3: Skills
Finally, you enter the skills phase. You’ve done your research and know the jobs you actually want. So now you can really dive deep into 1 or 2 tools that are required. (It might be as simple as being an expert in using Excel. Huge numbers of organisations use this tool!).
However much experience you have, you will have a lengthy wait to hear back from job applications so this is a great time to focus on skilling up. You can then enhance your CV as you go. If you get an interview in the meantime, that’s great. If not, at least you are being far more strategic in your approach.
When you are in a data role you can then look at expanding your data skills further, again being driven by either what your business uses or what next role you want to secure. This approach will save you a lot of time, effort and frustration!
Result driven strategy
This strategy is designed to help you get results as quickly as possible. It’s easy to feel a strong sense of imposter syndrome at every part of your data career which is why I believe that people tend to over focus on skills. It becomes a comfort blanket in which you can keep learning and never really put yourself out there. It’s a completely natural response but we just need to be aware that there is a part of your mind trying to keep you safe and not encountering “failure”. When we start applying for jobs, the risk is that we don’t get the results we want. We’ll need to encounter not hearing anything, or being outright rejected. No matter what stage of your career you are at, I can assure you that it is never an easy process. However, in order to get where we want to in life we do need to step outside our comfort zones.
The power of mentorship and accountability
If you are finding it a challenge to make progress in getting started in your data career, you might find it helpful to consider mentorship. Having someone to talk things through with and be accountable to is extremely powerful. These conversations often help provide the momentum to get started and keep going.