The Long-Term Jobs Outlook: Growth Fields and Entry Roles

The long-term jobs outlook is bright for data scientists, yet today's market is low-hire and low-confidence. See how entry-level shares differ.

By Cosby Khosa · Published 25 October 2026

Key takeaways

BLS projects data-scientist employment to grow about 35% over the decade.
The writer calls today's market low-hire, low-fire and low-confidence.
Almost half of postings are still entry-level, but the change favours experienced applicants.
The entry-level share ranges from 4.5% of software postings to over 90% in personal care and home health.

The long-term jobs outlook looks bright in some fields and cloudy in others. A newsletter from Mark Hamrick, published on 19 October 2026 as The Hamrick Brief on Substack, holds both thoughts at once. It notes that the Bureau of Labor Statistics projects data-scientist employment to grow by about 35% over the decade, while today's market is low-hire, low-fire and low-confidence.

The piece adds a striking detail about entry-level work. Almost half of job postings are still entry-level, yet the shift favours experienced applicants. And the entry-level share varies enormously by field, from 4.5% of software postings to more than 90% in personal care and home health.

This article explains why a long-term outlook and a short-term mood can differ, how to read the entry-level shares, and what to do with the information. It is based on a search extract of the newsletter, so it limits itself to the facts that extract stated. The newsletter is an opinion and analysis piece by a financial journalist, so treat its interpretations as one informed view.

What the long-term jobs outlook says

The newsletter makes two main claims. The first is about the future. Official projections from the Bureau of Labor Statistics expect data-scientist employment to grow by about 35% over a decade. That is far faster than the average for all jobs.

The second claim is about the present. The writer describes today's market as low-hire, low-fire and low-confidence. Employers are not letting people go in large numbers, but they are not hiring much either, and workers do not feel sure about their prospects.

These claims can both be true. A long-term outlook is built on trends such as technology, demographics and demand for services. A short-term mood is built on fresh data, news and feelings. A field can be a strong bet for the next ten years and still be slow this quarter.

The practical message is to hold two time frames in mind. Plan your career with the long-term jobs outlook, but manage your job search with the short view. If you do, you can avoid both false hope and needless despair.

Why data-scientist employment is projected to grow about 35%

A projected 35% rise in data-scientist employment is a large number. It reflects the way organisations now rely on data to make decisions. Banks, hospitals, retailers, governments and technology firms all collect huge amounts of data and need people who can turn it into insight.

Projections of this kind come from models that use current employment, industry trends and expected demand. They are estimates, not promises. They can be revised, and they depend on assumptions about technology and the economy.

It is also worth remembering that job titles change. The roles that count as data scientist today may be split into data engineers, machine learning engineers, analysts and AI specialists tomorrow. Other data shows that postings for machine learning engineers are rising while postings for general analysts are falling in some data sets.

For anyone drawn to this field, the lesson is to aim for skills rather than titles. Statistics, programming, data handling, communication and a good grasp of a business domain will stay valuable even if the labels shift. Build these with real projects, and you will be ready for the growth that projections describe.

What low-hire, low-fire, low-confidence means

The newsletter adds a third word to the usual low-hire, low-fire description: low-confidence. The addition is important. It says that the mood of workers and employers is as much a part of the story as the counts of jobs.

Low-hire means that employers are adding few positions. Low-fire means that layoffs are rare. Together they give a market with little movement, which other reports describe as low-churn or frozen.

Low-confidence means that people do not feel sure. Workers worry about whether their jobs are safe, and job seekers doubt whether they will find work. Employers worry about costs and policy. Gallup's research points the same way, showing that perceptions that it is a good time to find a job have fallen in the US and Canada.

Confidence matters because it shapes behaviour. When workers feel unsure, they stay put and spend less. When employers feel unsure, they delay hiring and investment. That can make a slow market slower. When confidence returns, the effect runs in reverse.

You cannot control the mood of the market, but you can control your own readiness. Build skills, savings and relationships, so that your own confidence does not depend on headlines.

Almost half of postings are entry-level, but the shift favours experience

One of the most useful facts in the newsletter is that almost half of postings are still entry-level. That may seem to clash with other reports, which show entry-level postings falling and senior postings rising.

It does not clash. Both can be true. If the share of entry-level postings is large but is falling, the market is moving toward experience from a high starting point. The Indeed analysis on seniority found entry-level postings down 7.5% and senior-level postings up 14.7% year on year in May 2026. The direction of travel is clear, even if entry-level roles remain a big part of the total.

Another way to put it is that there are still many entry-level jobs, but each draws more applicants, and employers are more selective. Experienced workers may apply for roles once thought of as entry-level, which pushes beginners down the queue.

For early-career job seekers, the takeaway is that entry-level roles are still the biggest category. Do not give up on them. But set yourself apart with proof of skill, because you may be competing against people with more experience.

Why the entry-level share varies from 4.5% to over 90%

The most eye-catching figures in the newsletter are the extremes. In software, entry-level postings make up only 4.5% of the total. In personal care and home health, they make up more than 90%.

The reason is the nature of the work. Software employers often demand experience, since mistakes can be costly and training takes time. Personal care and home health roles are more often filled by people with little formal experience, and training is built into the job.

This variation changes how you should read any average. When someone says that almost half of postings are entry-level, the statement hides a vast spread. In some fields, nearly every ad is for beginners. In others, almost none are.

If you are starting out, the share tells you how open a field is to newcomers. A low share means you may need a degree, a portfolio or an internship first. A high share means you can start quickly, though pay and progression may be limited.

Use these numbers to choose a path. Decide whether you prefer a field with easy entry and slower growth in pay, or one with harder entry and higher rewards.

What the long-term jobs outlook means for early-career workers

For people at the start of their careers, the long-term jobs outlook offers hope and a warning. The hope is that growth fields exist, and that skills in data and technology can open doors for a decade or more. The warning is that the doors are narrow right now, because employers favour experience.

Make a plan with stages, using the long-term jobs outlook as your guide. In the first stage, focus on getting any role that gives you real responsibility, even if it is not perfect. In the second, deepen your skills and results. In the third, move into the role you have been aiming for.

Be ready to take a route that is not direct. A first job in a related field, such as operations, support or research, can be a stepping stone toward data work. The skills you gain, including handling data and working with teams, will help you later.

Build evidence along the way. Projects, certificates and a clear record of results all help. Employers who are selective want proof, not promises.

Finally, look after your confidence. A tough market is not a verdict on your worth. It is a condition that many others share.

What mid-career and senior workers should note

If you already have experience, the shift toward seniority is in your favour, but not without limits. Employers want proven people, yet they are cautious about adding cost.

Make your value clear. Show how your work has led to savings, growth or better quality. Highlight leadership, judgement and the ability to work across teams.
Keep learning. If data science and related fields are expected to grow, skills in data analysis, automation and AI tools will help you stay relevant in almost any field. You do not need to become a data scientist. You do need to be comfortable working with data.
Think about flexible routes, too. The Celarity post notes that firms increasingly rent senior expertise for defined problems. If permanent roles are scarce, consulting or interim work may be an option.
Stay visible. Share your knowledge, mentor others and keep your network active. In a low-confidence market, trusted reputation is a powerful asset.

What employers and HR leaders should take from the outlook

Employers face a trade-off. Hiring experienced people brings fast results, but a pipeline with no beginners can run dry. The newsletter's point that almost half of postings are entry-level suggests that many firms still rely on beginners, but that the balance is shifting.

HR leaders should think about where they sit on the spectrum. If you are in software, where only 4.5% of postings are entry-level, consider how you will grow talent for the future. Apprenticeships, internships and structured graduate programmes can help.

If you are in a field where most roles are entry-level, such as personal care and home health, consider how to retain people and create a path up. High turnover is costly, and clear progression can help.

Also think about the skills of the future. If data-scientist employment is expected to grow about 35%, competition for these skills will rise. Plan early, either by training your own people or by building a reputation as a good place to work.

How to read the long-term jobs outlook wisely

Projections are useful, but they are not fortune-telling. A few rules help.

Check the source and date. The Bureau of Labor Statistics publishes employment projections on a regular cycle, and they are revised. Look for the latest edition.
Remember the assumptions. Projections depend on expected technology, demographics and policy. If those change, so will the results.
Look at both growth rates and total openings. A fast-growing occupation with few jobs may offer fewer chances than a slower-growing one with many jobs. A 35% increase is a bigger story when the starting number is large.
Distinguish between occupations and titles. The same work can go under different names, and the same name can cover different work.
Combine projections with current data. A strong long-term outlook does not guarantee that the next quarter is easy.

These rules apply to any long-term jobs outlook, in any country. South African readers can use the same approach with local sources, such as national statistics and skills planning reports.

A simple plan for using the long-term jobs outlook

Turn the long-term jobs outlook into action with a simple plan.

Step one: choose a direction. Ask which fields match your interests and strengths, and check which have positive long-term prospects.
Step two: check the entry-level share. Find out how open the field is to newcomers, and what proof of skill employers want.
Step three: build skills. Pick two or three skills that appear repeatedly in job ads in your chosen field, and learn them with practical projects.
Step four: gather proof. Keep a portfolio or record of results that you can show.
Step five: widen your search. Look at adjacent roles and sectors to give yourself more chances.
Step six: review every quarter. Check the market, update your plan and adjust.

In short:

Choose a field with a positive long-term jobs outlook.
Check how open it is to beginners.
Build and prove two or three core skills.
Review your plan every three months.

Final thoughts

The long-term jobs outlook is bright for fields such as data science, with employment projected to grow about 35% over the decade, yet today's market is low-hire, low-fire and low-confidence. Almost half of postings are still entry-level, but the shift favours experienced applicants, and the entry-level share ranges from 4.5% in software to over 90% in personal care and home health.

For early-career workers, the plan is to aim for growth fields, build proof and be patient. For experienced workers, it is to show value and keep learning. For employers, it is to protect the talent pipeline.

Read the full newsletter for the author's own view of the long-term jobs outlook, and check the Bureau of Labor Statistics for the latest projections.

Sources and further reading

The Hamrick Brief (Mark Hamrick), The Long-Term Jobs Outlook