January 2026EPM Scientific
Biotech vs Big Tech: Why Purpose, Not Pay, Wins AI Talent
The new realities of hiring AI and data talent in Biotech
Biotech is now competing directly with Big Tech for AI and data talent, and the rules of hiring have shifted.
- AI and data skills now command higher salaries shaped by the tech sector, not life sciences.
- Purpose is one of the few differentiators biotech can offer that other industries cannot match.
- Hybrid profiles are rare. Most companies succeed by pairing strong AI talent with scientific experts.
- Candidates expect clarity, flexibility and modern working practices as standard.
- The companies that hire well are the ones that communicate their scientific mission clearly from the start.
Biotech companies are hiring into a very different environment today compared with the one they faced only a few years ago. As data, automation, and modern tools become standard across scientific work, biotech organisations now find themselves competing for the same talent that Big Tech, finance, and energy firms are pursuing. This competition between biotech and Big Tech for AI talent is reshaping how companies define roles, set salaries, and communicate purpose.
According to the World Economic Forum, 22% of current jobs are expected to undergo structural change by 2030, driven by advances in AI and the rapid spread of digital skills across industries. Many of the roles emerging from this shift sit where technical expertise, data handling, and applied problem solving meet. Biotech companies rely on this same talent to move research, development, and clinical programs forward.
The labour market has already placed a clear price on these skills. The International Monetary Fund, in its January 2026 analysis New Skills and AI Are Reshaping the Future of Work highlighted that job postings requiring new digital capabilities attract wage premiums of around 3% in the United Kingdom and the United States, rising further when multiple skills are combined. This sets a firm baseline. Competitive pay is now assumed rather than negotiated.
What influences decisions beyond that point is not a marginal increase in salary, but how clearly companies can show where and why those skills matter. In biotech, compensation gets candidates to the table. Visible purpose, modern working practices, and a clear link between technical contribution and scientific progress are what secure the hire.
For biotech hiring AI talent, salary is no longer the differentiator. Purpose is.
A different kind of talent for a different kind of Biotech
For many years, biotech companies hired computational scientists who came up through biology, chemistry, or a related discipline. That profile is still valuable, but it is no longer the only one that matters. As AI and automation become embedded in discovery and development, companies are now hiring people who may have no scientific background at all, but who can build the tools that make modern research possible.
These candidates often come from Big Tech environments where modern tooling, fast iteration, and high autonomy are standard.
Edward Curry, describes the shift plainly:
A few years ago, a biotech start-up would not consider hiring someone who knew nothing of biology. Today, if that person can build an AI that predicts protein folding or analyses pathology images, they are worth their weight in gold.
Our most recent Life Sciences Talent Report reflects this reality. 68%
of life sciences professionals say AI is already shaping their career or soon will. AI expertise is now a discipline, and biotech needs to it to move the science forward.
This widening talent pool is also the same one Big Tech, finance, and energy companies are drawing from. The competition is not theoretical. It is happening in real time, and biotech is no longer competing only with its peers.
The market Biotech is competing with
Perhaps the biggest adjustment for hiring managers is the salary level that AI and machine learning specialists now command. Senior scientists with strong computer science backgrounds can require an additional $100,000, and experienced ML talent in biotech can reach $250,000. These figures are shaped not by biotech alone, but by the salaries offered across the technology sector. Biotech is competing in a market it did not create but must now operate within.
Defining the role is another challenge. Some companies still hope to find candidates with deep AI expertise and deep biological knowledge.
Edward Curry is clear about the reality:
There is really no one who meets both deep AI and biology experience and would be open to a traditional biotech salary range. Most companies are better off prioritising one or the other.
Many organisations now hire strong AI specialists and pair them with scientific subject matter experts. This approach allows each person to focus on what they do best, while keeping the scientific purpose at the centre of the work. It is also a more realistic way to build teams in a market where hybrid profiles are rare and heavily sought after.
The result is a hiring landscape where salary matters, but clarity matters more. Candidates want to understand the scope of the role, the expectations, the level of autonomy, and how their work will connect to the science. When those elements are vague, even competitive pay struggles to compensate.
Purpose: Biotech's most enduring advantage
Purpose has always mattered in biotech. What has changed is the market around it. As salaries, flexibility, and modern working practices become more consistent across industries, purpose is one of the few factors biotech can offer that others cannot replicate.
People with strong technical skills know they can work in Big Tech, finance, or energy. What those sectors often cannot offer is the chance to apply those skills to work with direct scientific or clinical impact.
Luke captures this clearly:
The science is often one of the most important reasons someone will make a move, because they believe in the work or want to be part of something cutting edge.
A quarter of survey respondents say they would accept a salary reduction to work on GenAI projects making a positive impact. That reflects a desire to work on meaningful, technically challenging problems rather than incremental optimization.
For biotech, this is a genuine differentiator, but only when it is communicated clearly. Candidates want to understand the scientific context of the role, the problem they will help solve, and how their work contributes to real outcomes. When that story is visible, purpose becomes one of the strongest reasons people choose this sector over others.
Strategies for attracting Biotech talent
1. Budget realistically and stay flexible
AI talent is expensive. Firms that set unrealistic budgets often face long vacancies. Flexibility on compensation and openness to adjacent skills or non-traditional backgrounds can make a significant difference.
2. Lead with science and purpose
Biotech’s strongest attraction is its purpose. Candidates want to know the scientific question they will help answer. Show how their work would directly support a meaningful change.
3. Build pipelines and partnerships
Many strong candidates do not apply through standard job adverts. Recruitment partners who understand the AI and ML talent market in biotech can help identify people who are motivated by scientific purpose as well as technical challenge.
4. Develop internal taken and compensate accordingly
39% of biotech professionals completed AI training last year, yet only 10% received a pay increase. Supporting internal development can be a cost-effective way to build hybrid roles while strengthening loyalty and scientific continuity.
The shift leaders cannot ignore
Technical talent is choosing between industries that now look increasingly similar in salary, flexibility and tools. What sets roles apart is clarity of purpose and the chance to work on problems with real scientific weight. Hiring leaders who make that visible will win the people they need.
This is not a temporary squeeze. It is the new hiring environment. Organisations that adapt quickly will move faster, build stronger teams and stay ahead.
EPM Scientific partners with life sciences companies to help them compete for this talent and shape roles that attract the right people. If you want to strengthen your hiring approach or reach candidates who can deliver the science, our team can support you.
Request a call back to speak to one of our experts and see how we can help future-proof your team.
FAQs: Biotech vs Big Tech – Winning AI Talent
As AI and data skills become central to modern research, biotech is hiring from the same talent pool as Big Tech, finance, and energy companies. Candidates now expect competitive pay, modern tools, and flexibility.
Purpose is biotech’s strongest advantage. Scientific impact, meaningful work, and a clear link between technical contribution and research outcomes often outweigh salary in attracting top AI talent.
Most successful teams pair AI specialists with scientific experts. This allows each professional to focus on their strengths while keeping the scientific mission central to the work.
Clarity of role, flexibility, autonomy, modern working practices, and a visible connection between their work and real scientific outcomes are key factors in decision making.
Firms succeed by leading with scientific purpose, offering flexible budgets, supporting internal talent development, and partnering with recruiters who understand the AI talent market in life sciences.