bioinformatics scientist
Snapshot
Unlock the secrets of life's building blocks! As a bioinformatics scientist, you’ll combine your passion for biology with powerful computer skills to analyze data, build databases, and contribute to breakthroughs in fields like biotechnology and pharmaceuticals.
Bioinformatics scientists are at the forefront of modern biological research, bridging the gap between complex biological data and computational analysis. Your days might involve designing and maintaining databases of genetic information, writing programmes to analyze DNA sequences, or collaborating with researchers to interpret experimental results. This role requires a strong analytical mind, attention to detail, and the ability to communicate complex findings clearly.
- • Analyzing biological data using computer programmes and statistical methods.
- • Developing and maintaining biological databases.
- • Identifying patterns and trends in genetic data, potentially including DNA samples.
Unlock the secrets of life's building blocks! As a bioinformatics scientist, you’ll combine your passion for biology with powerful computer skills to analyze data, build databases, and contribute to breakthroughs in fields like biotechnology and pharmaceuticals.
Could bioinformatics scientist fit you?
Answer three quick questions. This is not a full assessment — it is a teaser to help you decide whether to compare your profile.
Do you enjoy tasks that require Attention to Detail?
Do you enjoy tasks that require Cooperation?
Do you enjoy tasks that require Analytical Thinking?
Future Outlook for bioinformatics scientist
The outlook for bioinformatics scientist is exceptionally stable. While AI tools will assist with daily tasks, the core of this role relies on human judgment, resulting in a high resilience score of 83.9%.
How are these scores calculated?
The Resilience Score (0–100) estimates how structurally protected this occupation is from automation and AI disruption, based on task-level analysis. Higher scores mean more human-judgment-intensive tasks. AI Exposure shows the estimated percentage of task hours that current AI capabilities could affect. These are model-derived structural indicators, not predictions about individual job security.
How could bioinformatics scientist change as AI adoption grows?
Human judgement, trust, and context remain strong protectors for this role.
How could bioinformatics scientist change as AI adoption grows?
Human judgement, trust, and context remain strong protectors for this role.
How AI may change this role
Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.
What still depends on people
This role remains strongly human-led where manage intellectual property rights depends on trust, nuance, and real-world judgement.
Where AI may become a co-pilot
AI is more likely to assist supporting tasks such as operate open source software, documentation, search, and workflow coordination.
Tasks most exposed to automation
Automation pressure appears selective rather than broad, with the strongest signal currently coming from Generative AI.
Detailed Analysis Vital Signs, AI Vectors & Megatrends
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Vital Signs, AI Vectors & Megatrends
Vital Signs
AI Exposure Vectors
0-100%Exposure to content generation, creative augmentation, and large language model tools
Exposure to workflow automation, decision-support software, and process digitisation
Exposure to AI-assisted analysis, pattern recognition, and predictive modelling tasks
Exposure to physical automation, robotics, and sensor-driven task displacement
Megatrend Signals
0-100%Model-derived scores. Indicates structural exposure to megatrends, not direct demand.
Technical Details
NexFuture™ v2.0 combines O*NET ability and activity profiles with ESCO skill group distributions and six global megatrend signals. Scores are probabilistic estimates, not guarantees. See the NexFuture™ Methodology White Paper for full details.
What people in this role usually do
Digital Technology
A typical day as a bioinformatics scientist
09 09:00 · Morning apply for research funding
10 10:30 · Mid-morning apply research ethics and scientific integrity principles in research activities
12 12:00 · Midday manage intellectual property rights
14 14:00 · Afternoon operate open source software
15 15:30 · Late afternoon analyse scientific data
17 17:00 · Wrap-up apply scientific methods
Task order is illustrative. Individual days vary.
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computational biology
The interdisciplinary scientific field that focus on employing data analytics and theories to investigate biological systems obtained through experiments.
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computational chemistry
The branch of chemistry that aims at addressing complex chemical problems through computer simulations.
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computer equipment
The offered computers, computer peripheral equipment and software products, their functionalities, properties and legal and regulatory requirements.
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database management systems
The tools for creating, updating and managing databases, such as Oracle, MySQL and Microsoft SQL Server.
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genomics
The field of study in relation to whole genomes of organisms, as well as their genetic or epigenetic sequence of information. It aims to provide knowledge about the downstream of biological products and the analysis of the structure and function of these sequences through employing recombinant DNA and bioinformatics approaches.
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web programming
The programming paradigm that is based on combining markup (which adds context and structure to text) and other web programming code, such as AJAX, javascript and PHP, in order to carry out appropriate actions and visualise the content.
- biology
- computer engineering
- computer programming
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promote open innovation in research
Apply techniques, models, methods and strategies which contribute to the promotion of steps towards innovation through collaboration with people and organizations outside the organisation.
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integrate gender dimension in research
Take into account in the whole research process the biological characteristics and the evolving social and cultural features of women and men (gender).
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conduct research across disciplines
Work and use research findings and data across disciplinary and/or functional boundaries.
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promote the participation of citizens in scientific and research activities
Engage citizens in scientific and research activities and promote their contribution in terms of knowledge, time or resources invested.
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manage findable accessible interoperable and reusable data
Produce, describe, store, preserve and (re) use scientific data based on FAIR (Findable, Accessible, Interoperable, and Reusable) principles, making data as open as possible, and as closed as necessary.
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perform scientific research
Gain, correct or improve knowledge about phenomena by using scientific methods and techniques, based on empirical or measurable observations.
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publish academic research
Conduct academic research, in universities and research institutions, or on a personal account, publish it in books or academic journals with the aim of contributing to a field of expertise and achieving personal academic accreditation.
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write scientific publications
Present the hypothesis, findings, and conclusions of your scientific research in your field of expertise in a professional publication.
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draft scientific or academic papers and technical documentation
Draft and edit scientific, academic or technical texts on different subjects.
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disseminate results to the scientific community
Publicly disclose scientific results by any appropriate means, including conferences, workshops, colloquia and scientific publications.
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collect biological data
Collect biological specimens, record and summarise biological data for use in technical studies, developing environmental management plans and biological products.
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synthesise information
Critically read, interpret, and summarise new and complex information from diverse sources.
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gather data
Extract exportable data from multiple sources.
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maintain freelance database
Maintain a freelance database that offers extra support to your teams and is able to calculate negotiating costs.
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perform data analysis
Collect data and statistics to test and evaluate in order to generate assertions and pattern predictions, with the aim of discovering useful information in a decision-making process.
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use databases
Use software tools for managing and organising data in a structured environment which consists of attributes, tables and relationships in order to query and modify the stored data.
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present reports
Display results, statistics and conclusions to an audience in a transparent and straightforward way.
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increase the impact of science on policy and society
Influence evidence-informed policy and decision making by providing scientific input to and maintaining professional relationships with policymakers and other stakeholders.
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manage research data
Produce and analyse scientific data originating from qualitative and quantitative research methods. Store and maintain the data in research databases. Support the re-use of scientific data and be familiar with open data management principles.
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manage database
Apply database design schemes and models, define data dependencies, use query languages and database management systems (DBMS) to develop and manage databases.
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promote the transfer of knowledge
Deploy broad awareness of processes of knowledge valorisation aimed to maximise the two–way flow of technology, intellectual property, expertise and capability between the research base and industry or the public sector.
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think abstractly
Demonstrate the ability to use concepts in order to make and understand generalisations, and relate or connect them to other items, events, or experiences.
Skill DNA
Work personality traits and values that define this role
See whether this role fits your Career DNA
Take the free Career DNA assessment to see how bioinformatics scientist aligns with your interests, work style, and future path. In less than 10 minutes, you will get a personalized fit signal and a roadmap for what to do next.
Scan to continue on mobileGrowth Pathways & Similar Roles
Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.
Where does bioinformatics scientist fit?
Similarity scores based on skill overlap from ESCO data.
Frequently asked questions
- What kind of background is typically needed to become a bioinformatics scientist?
- A strong foundation in biology, genetics, or a related life science is crucial. You’ll also need proficiency in computer programming (e.g., Python, R), statistical analysis, and database management. Many enter the field with a master's degree, though a bachelor’s degree with relevant experience can also be a pathway.
- How does this role differ from a data scientist in a purely tech-focused company?
- While data science skills are essential, a bioinformatics scientist’s work is specifically focused on biological data. You’ll be applying data analysis techniques to understand biological processes, genetic information, and related research, often within a scientific or medical context.
- What are the key work styles and values for success in this role?
- Success requires meticulous attention to detail (1.C.3.a), analytical thinking (1.C.1.a), a commitment to accuracy (1.C.5.b), a proactive approach to problem-solving (1.C.7.b), and the ability to work independently (1.C.5.a). You’ll also find satisfaction in intellectual challenges (1.B.2.b), contributing to scientific advancement (1.B.2.e), working with complex systems (1.B.2.f), and achieving impactful results (1.B.2.a).