a comprehensive list of everything you need to know to land your data data job...
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Here's the gist of landing your first data job...
Data analyst is the best first data job
Better than data scientist or data engineer. Those roles are too advanced, and the learning curve will eat months of your life.
Data analyst is the happy medium. You can become one in a couple weeks if I'm being honest. And you can become a data scientist or data engineer from a data analyst position later — you don't need the master's degree or years of programming first.
But "data analyst" isn't the only role
There's like a hundred different job titles that are basically data analyst roles applied to different industries.
Marketing analyst? That's a data analyst in the marketing industry. Financial analyst? Data analyst looking at financial and accounting data. Business intelligence engineer? Fancy title for a data analyst who mostly does SQL and dashboarding.
If you're only applying to jobs with "data analyst" in the title, you're missing probably seventy percent of the opportunities. Business analyst roles are super hot right now for whatever reason — tons of them, and they're basically data analyst jobs embedded in the business.
The foot-in-the-door jobs
If you're in the US making less than $55,000, there's actually better opportunities for you than data analyst.
These foot-in-the-door data jobs pay about twenty-two to thirty-two dollars an hour. Titles like data janitor, data entry, or my favorite — data specialist.
You're doing things with data but not necessarily analyzing it. Cleaning it, manually transcribing it, doing very light analysis, preparing data for the data analyst.
I like these roles because they're a lot easier to land than even a data analyst job. My whole philosophy is get your foot in the door as quickly as possible.
What you actually need to know
I went through sixteen thousand jobs to figure this out.
Excel is still the number one tool. Required in about 40% of all data analyst jobs. And the good thing is it's not that hard to learn — a lot of you have probably already used it, and you just need to add a few more things.
After that, SQL (Structured Query Language). It's the next most in-demand tool. It is a programming language, so if you've never done any coding it'll take a little time to get used to. But there's really only like 20, 25 different commands you need to know to land your first data job.
Spoiler alert: you don't have to know SQL to land your first data job. I didn't. You could land one with just Excel, or just SQL, or just a BI tool.
BI stands for business intelligence — fancy term for dashboarding. Tableau and Power BI are the big players.
That's really all you need. Excel, SQL, and a BI tool.
Python? Not required
Python is only required in like 17% of data analyst jobs, even senior roles.
So 80% of the time you don't have to know it. And when you're just getting started, your time is precious. You're taking kids to soccer practice, you're in school, you're working two jobs, you gotta mow the lawn.
If we don't have to learn Python right now, I don't think you should.
Here's the cool thing people don't realize: in the data world, you are expected to not know everything on the job. You are expected to learn on the job. You will get paid to learn.
The wrong question
Everyone asks "how do I learn these skills?"
That's actually the wrong question. The right question is "how do I get the job?" — because that's what we're learning the skills for.
I don't think you're doing Excel for fun on the weekend. It's to land a job so you can get paid, go on vacation, provide for your family, help your parents out, give your kids a better life.
My whole philosophy: learn the foundations, but then get a job and get paid to learn the advanced and intermediate stuff on the job.
The formula
When it comes to landing a job, there's a formula: how many applications you send out multiplied by your trust factor.
If you have a low trust factor and apply to one job, you get close to zero offers. If you're doctor data analyst with a triple PhD and thirty years of experience and apply to one job, your trust factor is high — you might get that one job.
The more jobs you apply to, the more offers you get. So how do we increase the trust factor?
That's where the SPN method comes in.
S-P-N
S stands for skills. You have to learn the skills. That's the bare fundamental.
P stands for projects in a portfolio. That's visual tangible evidence that you can do what the skills are. The portfolio is a website where you can say "here are examples of how I've already analyzed data in a couple different ways."
N stands for network. If I know you and my company's hiring, I'm gonna hire you because I know you. People hire people. We hire people we trust, and we trust people we know. Strangers equal untrustworthy.
If you're trying to land a data job and you're only focusing on skills, you're missing out on two-thirds of the equation.
The only two things working for you
When you're applying for jobs, really only three things are working for you:
Your resume. If you're the best data analyst on Planet Earth but your resume sucks, you're not gonna get past the applicant tracking system (ATS). The computer looks at your resume and decides if you're a good fit. These systems are stupid — they can't read tables, they don't like columns. Even if you're great and have two columns and tables on your resume, the ATS could be like "I can't read this, throw away." And you're frustrated wondering what's wrong with you when nothing's wrong except your resume format.
Your LinkedIn. 97% of recruiters use it. You need a good LinkedIn that explains who you are, shows your projects, increases your trustworthiness. If you don't have one, create it today and make sure it's optimized.
That's pretty much everything
That's literally the roadmap for landing your first data job. Easier said than done, I know. But at least you know the map.
And if you want a guide, and some friends to come with you - that's where The Accelerator might be a good fit for you...
And I'll be announcing something pretty exciting in next week's newsletter about it. I think you'll like it.
Let's just say Christmas is coming early this year. Stay tuned.
LATEST EPISODE
pretty much everything you need to know to land your first data job
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☹️ I'm lonely.
Every week I write this newsletter to like 45,000 people. Guess how many people write back?
🦗 cue chirping crickets sound 🦗
Pretty much 0.
Now I don't need 45k replies - ha! that that would be very overwhelming. But it's sending a newsletter is a pretty lonely activity I guess? Feels like I'm just talking to ghosts or bots or something.
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But maybe this is my fault. Maybe these newsletter issues aren't helpful? Or do they not feel personal? Or maybe I seem scary and non-approachable?
All valid options...but I'd like to fix that. So let's start over...
👋 Hi, I'm Avery.
I live in Utah. I like Pokemon (but only Gen 1 & Gen 2). I like sports (I play basketball weekly, played college soccer, and am training for my 3rd IRONMAN 70.3).
This is my phone number: 435-220-4203 (don't believe me? text it).
I have two young kiddos (3 & 1). I'm a Christian (church every Sunday, read scripture, pray, etc).
I like to travel. Lived in Spain for 3 months this year. Visited Morocco & Gibraltar while there.
For breakfast, I eat yoghurt with cashews & blueberries. For dinner, it's whatever my wonderful wife of 10 years makes me. And for lunch, it's leftovers.
What else do you want to know about me? I'm an open book.
... did that work ... ?
Am I less scary now? More human?
🤞 fingers crossed
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Hit reply. I dare you.
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Really, anything.
I just want to feel like I'm not shouting to 45,000 ghosts.
Oh, and to sweeten the pot, if you're participating in the bootcamp giveaway, I'll give you 10 more bonus entries for replying to this newsletter (anything).
Okay. Talk soon,
