Yo, I'm Matt Mike 👋

(yes, Mike is my actual last name).

My career path has been far from linear. Here are the cliff notes (that's still a thing, right?)

2015: graduated with an English degree
2016: became a teacher
2017: became a dean of students
2019: left education for B2B sales
2019: hated sales. took a pay cut to become an operations analyst
2021: got promoted to operations supervisor

2022 and onward: became a business analyst (FIRST DATA JOB). Started documenting the journey on social media where I now have a combined following of 100,000+ tech professionals. I've been through a few different data roles with progressive complexity and now do BI consulting while continuing to help others progress their tech careers through content.

Because of my background, I have a passion for helping people with non-technical backgrounds break into tech and advance their careers. My technical passion is business intelligence analytics.

🤝🏻 Brands: mjomike@gmail.com
🎥 YouTube: @mattmike
📩 Newsletter: https://thdatapoint.substack.com/

Matt Mike

Not 1, not 2, but 3 hernia’s repaired.

Had surgery the other day. 

Recovery has been brutal but I’m so glad to finally get this done. These hernias have been a major impairment to physical activity and a daily discomfort.

Super grateful to my wife who’s been taking care of me, the kids, and everything else while I hobble around like an old man.

Day 3 of a 6-8 week recovery✌🏻

Business Intelligence Developer 🤘 | BI & Analytics Consultant | YouTube @ Matt Mike | Helping non-tech professionals break into data and make $30k+ more with the Data Career Makers community

No alternative text description for this image

I've applied to 1,000s of jobs in my career.

Most led nowhere.

But the problem wasn't my resume or skills.

The problem was treating job hunting like a numbers game.

(the spray and pray method).

Applying to 50 jobs a week → exhausting.
Applying to 5 targeted opportunities → strategic.

Strategic job hunting = better interviews, faster offers.

Here's how I'd approach the job hunt in 2026 if I had to start over:

1. Build relationships before you need them

Most people wait until they're desperate to start networking. 

They send cold messages, ask strangers for referrals, and wonder why nobody responds.

This is backwards.

Instead I'd spend 30 minutes a day engaging with people in my target companies.

Comment on their posts, share their content, add genuine value.

When you build relationships first, opportunities come to you.

You don't need to beg for referrals when people already know your name.

2. Post content that showcases your work

Resumes can get lost or ignored.

LinkedIn posts are living proof of what you can do.

I'd post 3x a week about projects I'm working on, problems I've solved, tools I'm learning.

Not generic advice. Actual work.

This does two things: 1) it proves you know your stuff and 2) it makes you visible to hiring managers who are scrolling LinkedIn looking for talent.

3. Apply like you mean it

I'd rather spend 20 minutes on one application than 10 minutes on twenty.

For each role I'd research the company, customize my resume to match their exact needs, and write a cover letter that shows the value I bring.

Then I'd find the hiring manager on LinkedIn and send a short message explaining why I'm interested.

Most people won't do this because it takes effort.

But that's why it works.

tl;dr:

1. Network before you need it. 
2. Prove your skills publicly.
3. Apply with intention.

ps - got a vid on this topic publishing soon. check out my channel so you don't miss it: https://lnkd.in/dpMCPTmH

Career growth is not always linear.

I've switched jobs and changed careers more than most.
I've even taken steps back at times.

But every shift always moved me forward in the long run.

To better pay.
To a better role.
To a better field (for me).

You can feel lost when a job no longer feels right.

Or when you're let go.
Or you're burnt out

But sometimes you have to take necessary shifts.

And those shifts aren't bad.
Staying stuck in a bad place is.

So embrace the checkered past.

Or the shifting target.
Or the challenging circumstance

Those steps are necessary.

You're just on your way somewhere better.

Had a great time at our low-key Phoenix, AZ happy hour last night!

Awesome turnout. Got to meet some great people!

It was also my first time meeting in person a few people that I've known from LinkedIn for quite some time now.

Andrew Madson 
Madison Schott 
Monica Kay Royal (won't let me tag you for some reason???)

We're thinking of doing these quarterly. 

If you're in Phoenix and missed this one, hope you can make it to the next one!

___
PS - still recovering from my hernia surgery but I couldn't miss this. Really pushed myself to be there. Couldn't stay long due to the pain, but glad I made it :)

A lot happened for me in 2025.

I've talked about bits and pieces of it here on LinkedIn, but I just posted a full video about it for anyone interested.

I like doing these yearly check-in type videos.

It's just nice to process everything out loud.

https://lnkd.in/g8i8PDAe

PS - thanks to everyone for the well wishes on my recovery from surgery. Today is day 5 and I'm getting a little bit stronger each day :)

Open video: Data Analyst Year In the Life: 2 Moves, Lost My Dream Tech Job, and What I'm Changing in 2026 on youtu.be

Data Analyst Year In the Life: 2 Moves, Lost My Dream Tech Job, and What I'm Changing in 2026

There's a lot of talk about data and AI.

And I hear most from people outside of the data space about what will happen to technical jobs.

So, in this video I share my boots-on-the-ground take on the situation. What I'm seeing, researching, and hearing from my many peers around and above me in the data and AI space.

https://lnkd.in/gdmDtEJb

___
PS - getting back to a regular schedule with uploads. My goal for 2026 is actually to increase volume to 2 uploads per week. We'll see if I can manage that lol

Open video: Will AI Replace Data Analysts in the Next 10 Years? on youtu.be

Will AI Replace Data Analysts in the Next 10 Years?

You don't have to sound like an idiot anymore.



Check out Count here:
https://lnkd.in/gKFDZJgN

#countpartner

Some people call pie charts bad.

It's like the "Is a hotdog a sandwich?" debate of data viz.

But I think it completely depends on the context.

There's nothing wrong with pie charts inherently.

Comparing 2 values against each other is a great use case.

The problem shows up when you have too many values.

Too difficult to interpret quickly. 
Data labels get smushed together.

Can you see the data clearly?

The second they start getting smushed, swap the visual.

(rule of thumb is 4-5 values, but it depends)

Especially when your dashboard is already full of bar and column charts.

So if you're avoiding pie charts because someone told you they're bad:

1. Ask yourself how many values you're showing
2. Consider if variety would help your dashboard
3. Check if the data labels are readable
4. Then decide

Context matters.

Which camp are you in on this?

___
PS - I just started a community for people breaking into data careers. Check it out here (launch pricing still active): https://lnkd.in/gjY7-wyJ

The data job market looks different this year.

More data jobs than ever before, but also more saturated.

As someone who was laid off and on the job hunt again mid-2025, I have some thoughts on how I'd do it all again 2026. Especially if I was starting from scratch.

In this video, I cover those thoughts.

https://lnkd.in/gvPJxsbq

Open video: The EASIEST Way To Become a Data Analyst in 2026 (skills + portfolio + job search) on youtu.be

The EASIEST Way To Become a Data Analyst in 2026 (skills + portfolio + job search)

I just created a FREE tier for my community.

It gives you access to all community chats as well as a few helpful resources.

I don't know how long I'm going to keep a free tier. Might be a week, might be forever. But once you're in, you're in forever, even if I close the free tier later on.

Interested? Check out the Data Career Makers community here:

https://lnkd.in/gHdhtf9v

✌️

ps - the community has only been open for a week. There's lots of great stuff there already, but I have lots of plans for building this out and creating a ton more value.

Curious...

...also, feel free to leave suggestions in the comments if you have a different answer than in the poll :)

___
ps - i got one of these. we're steadily growing! you can check it out here: https://lnkd.in/gjY7-wyJ

What would be MOST important to you in a community dedicated to helping you land a job in data?

The author can see how you vote. Learn more

Prefer not to say - my opinions are my own

Quant development and Data Science models, on energy markets

Senior Quant Developer 

QUANT AI Lab

My team builds fraud detection systems with low latency, on data with big volume & velocity. Accompany the client in building the ML system.
My roles involve consulting, data science, ML engineering, and leading a small, brilliant, team.

Senior Data Scientist - Project Lead

M47 Labs

Helping ML come to life when you talk to a machine

Machine Learning Engineer 

Zurich Insurance Company Ltd

Helping build a portfolio of ML products in a great team: from data to cognitive service as efficiently as possible. 
Cloud, DevOps, big data & ML. Plenty of fun juggling all these hats so the client doesn't need to.

Machine Learning Engineer

Sopra Steria Next

Fraud detection in Public Administration (fiscal) & Insurance / Health sector - survival models, classifiers ... (python ML stack, orchestration, microservices API
NLP robots to help migrate large volumes of legacy source code (COBOL, DB2, JCL)

Senior Data Scientist - Team Lead

2C Consulting

Anti-Money Laundering project for a major bank: supervised and unsupervised algorithms to identify suspicious activity (Hive/Sqoop, python, R)

Data Scientist consultant

Grupo Garatu

ERP focused on Gas & Energy markets
Modelling Natural Gas demand at several horizons. Datamart
B2B communications: eg banking (ISO 20022, SEPA), CNMC energy standards
Full-stack developer (C#, SQL + LINQ, MVC, JavaScript)

Analyst Developer (C# full stack, SQL, energy)

Lantalde

Computer vision project, industrial CNC context (C++, OpenCV): low latency, concurrency

Analyst Developer (C++ low latency, computer vision)

Sabbatical leave

Studied 48 academic credits (ECTS) of a university Master in Mathematical and Statistical modelling
Information & Network security (420 hr + 200 hr practicum)

Student

Crèdit Andorrà

Sr Investment Manager / Quant

Looking for action where Cloud, ML and client meet

+ Cloud or on-prem, where do you need it?
+ Data Science: from data to information you can act on
+ ML & cognitive services: ask your data
+ Project management: hub between data & client
+ Quant models - once a quant, always a quant: help you find the right questions to ask

Cloud: Azure, GCP,  DevOps ... infra as code is powerful
ML: Python, Spark, R
Quant developer: C++, python 
Full stack dev: C# + SQL (LINQ, MVC, RAZR + JavaScript)
Functional approach helps reuse and sanity

taplio

The Battle

Matt Mike

Alfredo Urrutia

Followers

Posts

Engagements

Likes

Performance ScoreMatt Mike's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Matt Mike

Alfredo Urrutia

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Matt Mike's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreMatt Mike's LinkedIn Performance