What If We Could Map the Gap Between What Companies Need and What Schools Teach?

The Mindful Dollar  ·  AI Explained Simply 

What If We Could Map the Gap Between What Companies Need and What Schools Teach?

I’m building a workforce intelligence dataset to prove what everyone feels but nobody is measuring.

By Nasly Duarte

Calling It Out Isn’t Enough

In my last post, I broke down a job listing that asked one person to do the work of three — an Assistant Controller role carrying Controller and CFO responsibilities at entry-level pay. The response was overwhelming. Employees said that’s my job right now. Business owners said I didn’t realize I was doing that. Educators said we don’t have a way to see this.

That last response is the one that kept me up at night.

Because I’ve been having this conversation for a while now. I’ve spoken to workforce development organizations, school directors, program administrators, nonprofit leaders, and economic development professionals in Miami about this exact structural issue. The response is usually some version of acknowledgment followed by inaction — not because people don’t care, but because they don’t have the data to justify changing anything.

Anecdotes aren’t enough. Frustration isn’t a metric. If I want institutions to move, I need to give them something they can measure, present to a board, and build a curriculum around.

So I’m building it.

What Cybersecurity Taught Me About Workforce Intelligence

In cybersecurity, there’s a company called SpyCloud. They don’t wait for data breaches to happen. They continuously scrape the dark web, structure the raw data into threat intelligence, and deliver it to organizations so they can act before the damage hits. They turned chaos into a dataset, and that dataset became a product that protects millions of people.

That model stopped me in my tracks. Because the workforce pipeline has the same problem — just in a different domain.

Companies are posting job descriptions that reveal exactly where their operations are broken. That data is sitting in plain sight on Indeed, LinkedIn, and government job boards. Every single day, employers are telling us what they need — and if we look closely enough, they’re also telling us what they don’t understand about what they need.

Meanwhile, schools are building curricula in silos. An accounting program teaches accounting. A project management program teaches project management. An IT program teaches IT. But the job market isn’t hiring in silos anymore — companies want people who can operate across all three. And nobody is measuring that mismatch at the local level where it matters most.

What if we could do for workforce development what SpyCloud does for cybersecurity? What if we could scrape, structure, and analyze job postings to create a real-time intelligence feed that shows schools, workforce programs, and economic development offices exactly where the gaps are?

The Gap Nobody Is Measuring

Let me be clear about what doesn’t exist right now.

The Bureau of Labor Statistics tracks broad occupational categories. LinkedIn publishes national hiring trends. The Department of Economic Opportunity releases workforce data at the state level. These are useful for understanding the macro picture.

But none of them do what I’m describing.

Nobody is taking actual job postings from South Florida employers — the ones posted this week, this month — and breaking them apart responsibility by responsibility. Nobody is counting how many distinct roles are compressed into a single title. Nobody is comparing the required skill combinations against what local programs actually teach. Nobody is scoring the alignment between what employers demand and what graduates are prepared to do.

Not in Miami. Not anywhere that’s accessible to the people making curriculum decisions at the institutions that feed our local workforce.

This means program directors are designing courses based on industry standards from five years ago, advisory board feedback that comes once a quarter, and their own professional experience — which may or may not reflect what’s happening on the ground right now. They’re building planes without radar.

What This Kind of Analysis Would Actually Show

Let me paint a picture using the job post I analyzed in my last blog as a starting point.

That one posting contained responsibilities spanning three distinct finance roles. It required proficiency across four different software platforms. It listed 16 separate duties. The salary topped out at $90,000 for work that, properly distributed, would cost a company $275,000 or more in combined headcount.

Now imagine running that same analysis across every accounting, finance, and operations job posted in Miami-Dade, Broward, and Palm Beach counties over the last 12 months. The dataset could surface patterns like:

Metric	What It Reveals
Role Compression Ratio	How many distinct roles are packed into a single title. A ratio of 3:1 means one person is expected to do three jobs.
Skill Mismatch Score	The percentage of required skills in a job post that are not covered by the corresponding local degree or certificate program.
Salary-to-Scope Alignment	Whether the pay offered matches the actual scope of responsibilities — or whether employers are buying three roles at one role’s price.
Curriculum Coverage Gap	The specific skills and competencies that appear frequently in job postings but are absent from local program curricula.
Technology Stack Drift	The software and platforms employers require versus what schools train students on — exposing how far behind training has fallen.

These aren’t opinions. They’re measurable, repeatable data points. And they give decision-makers something they’ve never had: a real-time map of the gap between the workforce pipeline and the workforce reality.

How You Actually Build This

I’m an AI student at Miami Dade College studying Computer Vision and Natural Language Processing. So let me walk you through what this looks like under the hood — in plain language, because the people who need this tool aren’t engineers. They’re educators, workforce developers, and business leaders.

Step 1: Collection. A web scraper pulls job postings from Indeed, LinkedIn, and government job boards, filtered to Miami-Dade, Broward, and Palm Beach counties. It collects the title, salary range, responsibilities, required skills, preferred qualifications, and industry. This runs continuously, building a living dataset that grows every day.

Step 2: Classification. A Natural Language Processing pipeline reads each job post and extracts the individual responsibilities, required skills, and software requirements. It doesn’t just count keywords — it understands context. It knows that “support the annual budgeting process” is a CFO-level responsibility, not an admin task. It classifies each responsibility by role tier and skill domain.

Step 3: Scoring. A comparison model maps the extracted skills and responsibilities against published curricula from local institutions — what MDC teaches in its accounting program, what Miami Tech Works covers in its workforce training, what certificate programs include in their course outlines. The model generates a coverage score: what percentage of what employers are asking for is actually being taught?

Step 4: Visualization. A dashboard presents the findings in a format that non-technical stakeholders can act on. Program directors see which skills are missing from their curricula. Workforce developers see which industries have the widest gaps. Economic development offices see where training investments would have the highest return. Employers see how their job posts compare to market norms.

This isn’t theoretical. Every component I just described uses technology I’m already working with in my AI program. The NLP pipeline, the classification models, the data architecture — these are the same tools I’ve been building with. The difference is the application. Instead of analyzing health data, I’m analyzing the health of the workforce pipeline.

Who Gets What From This

One dataset. Multiple stakeholders. Each one gets something different.

Schools and colleges get a real-time curriculum audit. Instead of relying on advisory boards that meet twice a year, program directors can see which skills are appearing in job postings right now and compare that against what they’re teaching this semester. They can identify gaps before students graduate into them.

Workforce development programs get targeting precision. Instead of broad assumptions about what industries need, they can see exactly which skill combinations are in demand and build training programs that match the market — not the market from three years ago, but the market from this month.

Economic development offices get ROI data for training investments. If the dataset shows that 80% of construction accounting roles in South Florida require ERP integration skills and zero local programs teach it, that’s a clear, fundable gap. It turns “we need more workforce development” into “we need this specific training program and here’s the data proving demand.”

Employers get a mirror. The dataset can show them that their job post is compressing three roles into one, that their salary is misaligned with their scope, or that the skills they’re requiring don’t exist in the local talent pool because nobody is training for them. Some won’t want to hear it. The best ones will use it to restructure their hiring and finally build the systems they’ve been trying to replace with people.

Students and job seekers get visibility. They can see what the market actually demands before they invest two years in a program. They can identify which additional skills would make them competitive. And they can walk into interviews with a clearer understanding of whether a role is structured fairly or whether they’re being asked to carry a department on their back.

I’m Building This in Public. And I Want You in the Room.

I’m not waiting for permission. I’m not waiting for a grant. I’m not waiting for someone to greenlight a study. I’ve been talking to organizations about this problem for long enough to know that the conversation alone doesn’t move the needle. Data does.

So I’m building this. I’m documenting the process. And I’m sharing it openly because the only way this works is if the people who need it can see it, challenge it, and shape it alongside me.

This isn’t about pointing fingers at any one company or institution. The construction company in my last post isn’t the villain — they’re building water treatment infrastructure that communities depend on. The schools aren’t failing — they’re working with the information they have. The workforce programs aren’t broken — they’re doing the best they can with incomplete visibility.

The problem is that nobody has given any of them a tool that shows the full picture. That’s what I’m building.

To educators and program directors: If you could see a real-time dashboard showing exactly which skills employers are demanding that your program doesn’t cover — what would you change first? What’s stopping you from changing it now?

To business owners and hiring managers: Would you use a tool that analyzed your job postings and told you whether you’re asking for one role or three? Would it change how you hire — or how you build your internal systems?

I want both sides of this conversation in the same room. Because the gap between what companies post and what schools prepare students for isn’t going to close itself. Someone has to build the bridge.

I’m building it. Come watch. Better yet — come help.

Nasly Duarte is an AI Solution Architect and accounting strategist based in Miami, FL. She’s currently studying Computer Vision and NLP at Miami Dade College while building tools that bridge the gap between workforce development, education, and the real demands of the job market. Follow her build-in-public journey on Buy Me A Coffee and LinkedIn.