How Much Experience Do I Really Need For An Entry Level Data Analyst Role?

Ladder to the sky

A Question From The Floor.

I’ve been answering a few questions over on Reddit recently for young graduates. Most are finding it tough to get their foot onto that first rung of the data analyst career ladder and need some guidance.

One that I thought might do with a little more detail was this:

For applications which say “you should be proficient in these” should I not apply to them if I don’t think I’m proficient? Like on applications do they really mean it when you say you need X level of experience with a certain language, or X years experience in the industry?

ANSWER:

It depends on the level you are applying for. For an entry level post I think it’s bad form to ask for X years experience. The whole point of recruiting at that level is to bring people in and train/mould them from the ground up. It’s not about spending a year breaking the bad habits they’ve picked up elsewhere.

Worst is when when lazy recruiters advertise posts looking for X+ years experience in a technology that has only been picked up in the wild for a couple of years. Especially when they ask for this at a junior or entry level. Come on, give people a chance!

If it asks for proficiency then let the interview panel be the judge of how proficient you are. Don’t BS people and say you are an expert when you’ll quickly be shown up on the first day on the job. But don’t self-defeat yourself and let a bit of imposter syndrome work against you either.

Provided you have actually gotten some experience, I think a willingness to learn and be open to new challenges is more important. This could range from just having opened the app to have a poke around to doing a college or side project on your own time.

Will this always apply?

Senior roles are different as you are expected to hit the ground running. I would be looking for those X years experience in a similar role or one with overlapping skills. The proficiency level would need to go up to actual regular use as well. If not in the exact tool or language then in something where the understanding is similar. For example, if not Tableau then Qlikview. If not R then SAS or Python.

When I interviewed at $DAYJOB they told me that SAS knowledge was extremely desirable. They knew however that there was a very limited talent pool in Ireland that actually had that kind of SAS experience. If I’d been put off by that requirement I would never have even applied. But they took a shot that my SQL, database dev and programming background would get me through and they were right.

It was over two years before I wrote a single line of SAS code. Funnily enough, no-one we hired in between was a SAS expert either. We got several damn fine analysts that added a HELL of a lot of value though which shows that hiring shouldn’t be a strict, rigid affair.

Show, Don’t Tell. But Tell As Well. Just To Be Sure.

Careers take many roads, twists and turns. It’s the job of the recruiting manager to realise that and pick out what you can bring to the table. They’ll only get that from what you tell them on your CV and in interviews.

For those just starting out, it’s about taking a punt on someone who gives you an inkling of what they could do rather than what they have done. That’s always much harder to spot. That’s why side projects are great options for showing what you can do. I’d use them to help open up a conversation as much as for the actual end result.

Ultimately, if you don’t make an effort to sell yourself then no-one else is going to do it for you. And that applies however many years you have on your personal career clock.

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