Where is the line? The real necessity of scientific backgrounds in tech roles across BioTech and Life Sciences

24 February 2026

By Julien Funes

The convergence of life sciences and technology has moved beyond buzzwords. Across Europe, Biotech, TechBio, Medical Device and research-driven organisations are scaling products that sit directly at the intersection of wet lab science and complex software systems.

And yet, one question continues to surface in hiring conversations:

How scientific does a software engineer really need to be?

This is no longer an academic debate. It’s a commercial one. The answer affects hiring timelines, salary benchmarks, product velocity and, ultimately, competitive advantage.

After years recruiting software engineers for scaling life science companies, one thing is clear: the line is shifting — and many organisations haven’t adjusted their hiring strategy accordingly.

1. The rise of “Domain-Embedded” engineering

Five years ago, many biotech companies were comfortable hiring strong generalist engineers and relying on scientists to “translate” requirements.

Today, that model is under strain.

Whether it’s:

AI models trained on biological datasets
Software embedded in regulated medical devices
Platforms supporting genomic workflows
Clinical data infrastructure

The margin for misinterpretation is smaller. Engineers are increasingly expected to understand experimental design, data provenance, regulatory constraints or biological context — not just implement tickets.

The result? A growing demand for “domain-embedded” engineers: professionals who can navigate both code and scientific nuance without constant mediation.

These profiles are rare.

And when companies insist on deep software expertise and advanced scientific credentials, they are narrowing their talent pool dramatically.

2. The talent availability paradox

Here’s the uncomfortable reality: there are not thousands of software engineers in Europe who also hold advanced degrees in molecular biology, bioinformatics, physics or biomedical engineering — and want to work in scaling environments.

Most sit in one of three categories:

Scientists who learned to code
Engineers who moved into life sciences and built domain exposure
True hybrids (often PhD-level with production-grade software experience)

Category three is extremely limited — and highly competed for.

Hiring managers often say they want someone who “understands the science.” The real question is: to what depth?

Is conceptual literacy enough?
Do they need to challenge scientific assumptions?
Will they sit in regulatory meetings?

The more senior or product-critical the role, the more domain depth becomes commercially valuable. But demanding it by default — even for infrastructure or platform roles — can extend hiring cycles significantly.

3. The impact on hiring strategy and workforce planning

This trend is reshaping how scaling companies must think about team design.

Three patterns are emerging:

Over-specification

Some organisations list PhDs as “preferred” for roles that primarily require backend architecture skills. This artificially reduces applicant flow and inflates compensation expectations.

Underestimating ramp-up time

Conversely, hiring pure tech talent without structured scientific onboarding often slows product development. Engineers spend months deciphering terminology, experimental logic or compliance frameworks.

The hybrid team model

The most effective teams I see are structured deliberately:

Core engineers with strong technical depth
A subset of domain-heavy technologists
Clear cross-functional communication processes

Not every engineer needs a scientific degree. But someone in the room must deeply understand the science, and the tech team must be close enough to it to build intelligently.

4. Consequences for scaling companies

This is not just about CV screening.

It directly affects:

Product timelines – Misalignment between science and engineering slows iteration.
Regulatory risk – Particularly in medical devices, misunderstanding requirements can be costly.
Investor confidence – Leadership teams increasingly scrutinise technical depth during due diligence.
Retention – Engineers without context often disengage in highly scientific environments.

Companies that clarify where scientific depth is truly essential, versus where structured collaboration suffices, hire faster and scale more effectively.

So where is the line?

The line is not fixed.

It depends on:

The proximity of the role to core scientific IP
The regulatory environment
The maturity of your engineering function
The communication capability of your scientific team

But here’s the strategic question I encourage leadership teams to consider:

How many people do you actually know who can genuinely operate across both science and production-grade engineering?

If the answer is “very few,” your hiring expectations need to reflect market reality — or your recruitment strategy needs to be highly targeted.

Final thoughts

Europe’s life science ecosystem is producing extraordinary innovation. But the intersection of science and software is not an infinite talent pool. It is specialised, nuanced and competitive.

The companies that win are those who:

Define clearly where domain depth is mission-critical
Design team structures intentionally
And access talent networks that sit precisely at this intersection

I specialise in working with software engineers operating within life sciences and the organisations building at that edge. If you are assessing whether your hiring expectations match the realities of the market, I’m always open to a conversation.

Because the real challenge isn’t whether scientific background matters.

It’s understanding when it truly makes the difference.

About the author

As a Senior Recruitment Consultant at Aspire Life Sciences, Julien Funes’ expertise lies at the nexus of technology and life sciences. He recruits top Software Engineers and data talent for Biotech and life sciences startups across Europe and North America. He is committed to advancing the industry by sourcing and securing top-tier talent for roles in these critical sectors. His approach enables him to effectively match candidates with opportunities where technological innovation meets life science excellence.