Lira Nigmatullina is a life sciences professional who transitioned from academia into roles across consulting, biotech, and product management. With experience in scaling R&D organisations and working at the interface of science and industry, she now supports researchers as co-founder of BeyondAcademia. Drawing on her background as a hiring manager and career coach, she shares insights into what hiring managers look for in researchers and how scientists can navigate careers beyond academia.

You moved from academia into industry. What initially motivated your transition out of academic research?

There were two main reasons.

First, as a non-EU citizen working in Germany and Italy, I constantly had to worry about my visa status. Academic contracts are typically fixed-term, which means frequent interactions with immigration authorities and long-term uncertainty. I was looking for more stability and the possibility of a permanent contract, which industry could offer.

Second, I realized that academic science is often highly individualistic. Success depends on competing for authorships, grants, and recognition. Over time, I found that this environment did not align with my values. I wanted to work in real teams, build things together, and contribute to shared outcomes rather than continuously competing for individual achievements.

As a former hiring manager: What made a strong application stand out? What were common mistakes?

From my experience as a hiring manager, three things make a strong application stand out.

1) A strong application is clear both to the recruiter and to the hiring manager.

As a hiring manager, I don’t have time to review every application in detail. And this is not my primary job.

The main work of finding and pre-screening candidates is done by recruiters, and I rely on their expertise. An important fact is often ignored: HR and talent acquisition managers usually do not have a degree in Life Sciences (most likely they studied business or psychology), and they typically do not have a PhD.

So when a CV highlights a very specific academic project like:

“Cyclin A2/cyclin-dependent kinase 1-dependent phosphorylation of Top2a required for S-phase entry during retinal development in zebrafish,”

it does not necessarily help recruiters understand your skills.

Recruiters do not have time to investigate how your research might translate into industry roles. They are searching for clear keywords and competencies relevant to the company.

The same experience can be translated into language that HR understands, for example:

• Cell cycle regulation
• Protein expression, purification and characterisation
• Genome instability studies
• In vivo functional studies

So if you want your application to reach a hiring manager like me — a biologist with a PhD — you first need to make sure the recruiter can understand your CV.

2) Strong applications show evidence, not just claims.

Academics are trained to think critically, they don’t believe unsupported statements.

But interestingly, many academic CVs still contain claims without evidence.

For example:

“I developed Python tools for scalability of pipelines, ensuring stable results.”

“Scalability, stable results” sound nice, but there is no evidence for that.

As a hiring manager, I want to see the prove how the candidate achieved the result.

This description gives me the prove for “scalability and stability” claims:

“Reduced production code deployment time by 80% by automating code releases using CI/CD and Docker technologies while ensuring production code stability.”

3) A strong application provides context.

Statements such as:

“Results-driven, goal-oriented, passionate scientist aiming to bridge data analytics with innovative solutions in fast-paced environments”

do not tell me anything. It sounds generic and looks AI-generated.

Instead, describe your experience using the What – How – Result framework.

For example:

“Conducted cytotoxicity tests on human fibroblasts and evaluated anti-human cytomegalovirus activity (plaque assay and qPCR), identifying 2 prototype drug candidates from a library of 1,300 FDA- approved compounds.”

This sentence clearly shows:

• What was done —cytotoxicity and anti-human cytomegalovirus activity studies
• How it was done — plaque assay and qPCR
• Result — identification of 2 prototype drug candidates from a library of 1,300 approved compounds

Many researchers struggle to translate academic achievements into language industry employers understand. How can candidates reframe their expertise?

To reframe academic experience into “industry”-friendly language, I would recommend addressing three common gaps:

First, many candidates lack a clear understanding of the role they are applying for. For example, “project manager” and “product manager” may sound similar, but they are fundamentally different roles with different expectations. The same CV cannot be used for both. Before applying, candidates should research the role carefully and understand what the job actually requires.

Second, many researchers misunderstand their own industry-relevant skills. Not everything that mattered in academia is valued as highly in industry. For example, scholarships, supervisor names, or publication lists are often less important.

At the same time, skills that were sometimes undervalued in academia—such as collaboration, coordination, troubleshooting, stakeholder management, or people leadership—are highly valued in industry.

Third, even when researchers understand how to translate their experience, many feel uncomfortable doing so, as if they were exaggerating or “selling themselves”. For example, what academics describe as “maintaining lab notebooks” can be framed as “ensuring data traceability,” or “participated in conferences” as “promoting visibility and establishing connections with key opinion leaders”. This is not about exaggerating or „faking“. It’s about showing how your skills are transferrable into industry.

What are the key signals interviewers look for when meeting candidates from academia?

The main signals I looked for were maturity, clear and concise communication, a growth mindset, and the ability to work in teams.

Maturity means the ability to reflect, take responsibility for outcomes, show reliability, and demonstrate emotional intelligence.

Clear communication is essential because, unlike academia, industry requires interaction with many different non-scientific departments —clients, investors, sales, business development, production, and more.

A growth mindset is critical: the ability to learn continuously, adapt to complexity, and question one’s own assumptions.

Teamwork is non-negotiable. In industry, success is never achieved alone by “working harder in the lab.” It requires trust, delegation, and collaboration.

At the same time, many academics carry unresolved stress or negative experiences from their PhD. This nervousness or low energy can often be sensed by the hiring panel. If someone struggles with trust issues or social interactions, it is important to take care of mental health first, rather than expecting a new industry job to solve these problems. Companies tend to hire people who bring positive energy and enthusiasm to the team.

To prepare for interviews, I strongly recommend developing STAR-structured examples that demonstrate teamwork, problem-solving, accountability, and the ability to learn from mistakes.

Researchers often don’t know which roles they are actually qualified for. How can they identify suitable positions?

One important thing to accept is that no industry role will be a 100% perfect match after years in academia. And that is totally normal!  Academic training prepares researchers primarily for a professorship, not for industry careers. Industry roles will feel unfamiliar at first, even research positions in pharma.

Instead of feeling frustrated, I recommend the following:

Talk to industry professionals to understand what it is like to work in their specific role and what success looks like in practice, even if the job titles or goals sound far from academic tasks. I would have never ended up as a Computerised system validation consultant, if I wouldn’t know people in industry who explained their job in validation departments to me.

Follow professionals on LinkedIn or YouTube who openly talk about their work—such as sales specialists, field application scientists, spatial biology experts, or scientific illustrators. Engage with their content and learn how they describe their roles.

Seek professional career coaching from people with real hiring and recruiting experience in industry. External perspectives are often crucial. I frequently see candidates who believe they should be bioinformaticians or R&D scientists, but who are actually much better suited for customer-facing roles such as field application scientists—or vice versa.

What patterns do you observe among your clients who transition successfully?

From my experience working with many researchers who successfully transitioned into industry, the key pattern is mindset.

The people who move faster are those who are ready to change their perspective. They are willing to unlearn some of the assumptions they developed in academia, question their previous beliefs about careers, and adapt to a very different environment.

They are also comfortable with uncertainty and vulnerability. Transitioning into industry often means entering unfamiliar territory, learning new rules, and becoming visible to industry people.

Another important factor is ownership of the transition. The candidates who succeed usually understand that industry does not owe them a position simply because they have a PhD or strong academic achievements. They don’t talk in a negative or disappointed or sarcastic way about industry. Instead, they focus on learning how industry works and what companies actually need.

This includes understanding the market, learning how to communicate their skills in industry language, and actively engaging with professionals outside academia.

And this brings me to one of the strongest predictors of success: networking.

Many academics spent years prioritizing their thesis, publications, and academic reputation — which is completely understandable. However, it also means that their professional network often remains limited to academia.

People who already have a network outside of academia, or who start actively building one, tend to find opportunities much faster (2-3 months compared to 6-12 months). They gain insights into industry expectations, receive referrals, and become visible to hiring managers.

Those who avoid networking usually face a much longer process, often experiencing many rejections or simply being ignored during online applications.

So overall, the successful candidates are the ones who stay curious, take responsibility for their transition, and actively build connections outside their academic bubble.

Finally, what message would you share with researchers who hesitate to step outside academia?

My main message is that your next step does not have to define the next five years of your career.

The industry world is dynamic. It is very normal to change two or three roles within five years, and that is completely fine. Careers outside academia are much more flexible than many researchers expect.

It is also okay to experiment. Someone might start in a role like marketing or consulting and later return to R&D.

In my experience, the most difficult step is the transition itself — moving from academia into the first industry role. Once you are inside the industry ecosystem, future transitions become much easier.

For researchers who feel uncertain, I often recommend the book Working Identity by Herminia Ibarra. The book explains that career change rarely happens through one perfect decision. Instead, it happens through small experiments, trying new roles, meeting new people, and gradually discovering what fits.

So if you feel that your career needs a new direction, you do not need to have the entire path figured out. You only need to take the first step and stay open to learning along the way.

And finally, for researchers in Germany who feel stuck in their transition, we also run a career coaching program specifically designed for PhDs and postdocs moving from academia into industry.

The program focuses on helping Life Sciences academics clarify their career direction, translate their academic experience into industry-relevant language, develop strong application materials, and build effective networking strategies.

For eligible candidates in Germany, this coaching can be fully funded through the AVGS voucher (Aktivierungs- und Vermittlungsgutschein) provided by the German Federal Employment Agency.