Roles and responsibilities

The job titles and the tasks associated within industry research are quite diverse. In particular, there can be large differences depending on if the company is a start-up or more established company.

Possible tasks may include a subset of the following activities:

• planning relevant experiments and/or coding/analysis for projects you are involved in.
• depending on the role/hierarchy of the organization you work in, there may be staff who you can delegate (some or all) routine experiments and analysis to, but many roles do still involve some time at the bench.
• meeting with/communicating with colleagues and collaborators to discuss results, priorities, next steps etc.
• remaining up to date with domain/technology developments (e.g. reading the literature, attending conferences etc).
• writing scientific publications to disseminate the work.

at the lab head/more senior levels:

• oversee the research strategy and direction of the team’s projects.
• mentor and support career development of team members.
• report progress to management and other stakeholders, justify projects and budgets.
• propose new projects and directions that align with company priorities, presenting these to decision-makers.
• establish and manage external collaborations (including with academic labs)
• manage the lab budget and provide an organizational framework – or delegate/oversee this; ensure that the group follows scientific good practice (ethics, data management, appropriate experiment design and analysis including relevant standard operating procedures [SOPs]).
• in some start-ups: apply to European project funding.

Major differences to academic research include more team-based work, a faster turn-over of projects and a focus on a viable end-product rather than on grants and publications. Procedures are also often more standardized, which is particularly important when the resulting data will be included in an application for regulatory approval, or the analysis or production pipeline will be part of the end-product.

Career entry and progression

The exact job titles vary a lot between companies. In start-ups, the job titles may appear more senior to those with similar responsibilities in a larger company. Therefore, when applying to positions do research the company in advance and read the job advertisement carefully.

 A rough guide to entry-point job titles for pharma and biotech is provided below.

• Associate scientist
  • focus: carrying out bench-based lab work and/or data-analysis
  • typical entry requirement: master’s degree
• Postdoc
  • temporary scientist role focussed on hands-on bench/computational work; generally works on a main project that can be published.
  • typical entry requirement: PhD degree; also possible entry point for scientists with some academic postdoc experience
• Scientist or investigator (including specific titles like ‘computational biologist’)
  • scientist role requiring hands-on bench/computational work, plans own work independently
  • typical entry requirement: PhD degree; also possible entry point for scientists with some academic postdoc experience
• Senior scientist
  • focus on bench/computational work; but involves more independence/ideation. Often involves overseeing the work of technicians or junior staff (e.g. the experimental design and interpretation of results) but typically not as their direct manager.
  • Typical entry requirement: PhD and often 2+years of relevant additional experience. More rarely entry point directly after the PhD.
• Principal scientist or lab head
  • minimal bench/computational work and a workload including more supervision, operational management and research strategy tasks; usually leading a small team.
  • typical entry requirement: PhD and multiple years’ relevant experience, evidence of mentoring/supervision often required.

Based on our career tracking study, we estimate that 70% of EMBL alumni who enter industry research role remain in this career area, often rising through the ranks to more senior positions. A small percentage (around 10%) return to academic research, with around half of those directly entering – or progressing to – group leader roles, and the other half working in core facilities or other research positions. Around 15% of those who enter industry research move into other non-research roles – mostly within the life science industry (for example, business development, regulatory affairs, medical affairs) – or occasionally academic/public sectors (e.g. tech transfer, science management). A small fraction (around 2%) move into roles outside of science.

Knowledge and skills

Your technical expertise or domain knowledge are a key skill for industry. Teamwork and the ability to communicate with scientists from other disciplines are also highly sought after. This is because, in general, research in industry is highly collaborative and interdisciplinary; it is common to have so-called ‘matrix’ structures where members from different teams work on projects, and you are likely to have multiple projects where you provide specific expertise, working with a different collection of experts on each project.

In our careers and skills survey, 16 industry group leaders told us about the competencies they used most often. The most commonly selected competencies were:

• broad scientific knowledge (selected by 70% of respondents)
• resilient problem solving (selected by 65%)
• clarity of thought (selected by 60% ; and ranked as the most important factors for success, for those respondents)
• teamwork (selected by 55%)
• mentoring and leadership (selected by 55%)

For those in research staff roles (n=15), the most commonly selected competencies were:

• teamwork (selected by 61%)
• resilient problem solving (selected by 56%)
• broad scientific knowledge (selected by 56%)
• organization (selected by 44%; and ranked as the most important factors for success, for those respondents)
• clarity of thought (selected by 44%)

Language requirements

In our careers and skills survey, 26% of those working in industry research in a country where English was not the main language needed to be fluent in the local language; 26% reported that some knowledge was needed; and 47% could work without it.