Two years hunting for a local SEO analyst role - anyone else?

backlinker

Honestly, I've been grinding for a proper data-heavy local SEO role for over two years now. Managed to interview with 20+ companies - multiple HM rounds, final rounds. Still nothing sticks. Twice I got to the final stage, then they went with someone else or the budget vanished. No clue what I'm doing wrong.

At this point I'm running my own scripts to scrape Google Maps for ranking data and automating reports in Python just to keep my skills sharp, but it's soul-crushing watching younger grads land roles and move up while I'm stuck in neutral. Currently trialling Wonsulting's Ultimate Plan - happy to report back if anyone's curious.

Anyone else in the same boat? What's worked for you?

For context, one reply suggested just taking any job in the meantime - but when rent's due, you don't have the luxury of being picky. Another said stop begging and build a no-code tool to sell to the same companies rejecting you. that's a bit wild, but the idea of turning your current job into a data gig - tracking team metrics, building dashboards, networking with internal analysts - that actually resonates. courses never impressed anyone. Real projects and fundamentals do.

pixelpusher

2 years, same. but "grinding" won't pay rent. Take a job, sure, but treat it as a growth experiment, not a fallback. career is a luxury when you're broke - so be ruthless, not patient.

marketingmule

Totally feel you on this. It's rough out there when every job listing wants 3+ years of experience with tools you've only touched in a course. What worked for me was basically turning my day job into a data playground.

In paid social, you've got a goldmine of performance data - CTRs, ROAS, frequency, all that. Started tracking my own campaign metrics manually, cleaning up export messes in Sheets, building little dashboards for fun. Showed my manager and asked what KPIs they actually cared about. Half the time they didn't even know what was possible, so you end up defining the metrics yourself.

If your company has a data warehouse and offers BI tool licenses, grab that. Even if it's just non-sensitive audience data or revenue numbers. Chat up the analytics team - most of them love talking shop if you come with genuine curiosity. Offered to take some of their grunt work off their hands for real experience.

Courses? Meh. Projects and real-world stuff always wins. Use AI like a tutor - ask it to explain concepts, then go dig into the actual logic. Don't let it do the thinking for you.

Fundamentals matter more than ever. Too many people jump straight into automation without understanding why a join works or how aggregation affects numbers. Be the person who nails the basics and builds up from there. You'll stand out.

justauser

Honestly, the market is brutal right now for entry and mid-level data roles. If you've had twenty-plus interviews, it's not your background holding you back - more likely it's about positioning, telling your story in interviews, or simple timing and competition. Try not to compare your timeline to others too much, two near-offers is a sign you're closer than it feels. 💪

budgetburner

I tell everyone the same thing: go through a contracting company. No one's job is guaranteed anymore - that's a relic of the past, so full-time status isn't the golden ticket people think it is.

You'll lose some benefits depending on the agency, but it gets your foot in the door. Starting pay is usually higher, and if you like the place, converting to permanent is far easier.

I've done it three times now. Each time I landed a role within two months - even during the first wave of layoffs last June.

And no, LinkedIn's fine for applying. Never had an issue there.

socialbutterfly

I'd narrow it down way more than a generic data-science syllabus, honestly.

For every influencer partnership I'm evaluating, I keep a little scorecard:

📌 what the brand really wants to prove with this campaign
📌 which data source or engagement metric actually matters
📌 what baseline benchmark I'd trust first (e.g., their last three sponsored posts)
📌 one assumption that could totally mess up my ROI calculation
📌 how I'd explain the trade-off (reach vs. conversion) to the VP or client

Then I talk through it out loud for 20-30 minutes. Biggest win isn't memorising more frameworks - it's being able to explain the decision, metric, caveat, and recommendation without losing your cool under pressure.

bouncekiller

Stop begging for jobs. Build a no-code tool that scrapes data, automate reports, and sell it to the same companies rejecting u. Problem solved.

backlinker

Filtering by contract and just mass-applying? I've been through the same circus with data role recruiters. Plenty of initial contact, zero follow-through. It's a numbers game where most of them are just padding their pipeline.

pixelpusher

Training AI for peanuts? you're learning R and Python to land a low-paying contracting gig? that's the real joke. Dithering between data science and data engineering is a luxury when neither matters if you can't drive actual revenue. Specialise in something that solves a business problem-like analytics for scaling stores. moving cities won't fix a fuzzy direction.