Overview
At QIAGEN, we are driven by a simple but powerful vision: making improvements in life possible.
We’re dedicated to revolutionizing science and healthcare for the better. From our entrepreneurial roots to our current global presence, we've grown into a force for positive change. With thousands of employees across six continents, collaboration is our greatest strength. We’re always striving to identify talented individuals to join our exceptional teams.
We have played a pivotal role in shaping modern science and healthcare, and we're just getting started. If you're someone who thrives on new challenges, values diversity and wants to make a tangible difference in people's lives, then QIAGEN is the place for you.
At QIAGEN, every day is an opportunity to make a real-life impact.
Join us, grow with us, and together, let's shape the future of biological discovery.
About QIAGEN Digital Insights
QIAGEN Digital Insights is a global leader in providing bioinformatics solutions that empower researchers and scientists in the life sciences industry. Our innovative software tools enable the analysis and interpretation of complex biological data, driving breakthroughs in genomics, molecular diagnostics, and personalised medicine. We are passionate about our people, our users, our products, our technology, and our vision.
About the opportunity
We are seeking a dynamic and self-motivated Senior Data Scientist to join our team. The ideal candidate will play a leading role in designing and developing knowledge graphs and knowledge graph-based applications. The successful candidate will demonstrate a keen interest in exploring and adapting to emerging technologies and ideally possess a good understanding of the biomedical domain.
Your tasks
- Design, implement and maintain of biomedical knowledge graphs, supporting data stores and related applications.
- Develop and integrate analytical methods into production applications, potentially including graph algorithms, graph embeddings, link prediction, entity resolution, statistical inference, pathway analysis, and other computational biology methods.
- Evaluate emerging methods in knowledge representation, biomedical AI, and systems biology, and translate promising approaches into prototypes and production capabilities.
- Contribute to the design and implementation of applications that combine knowledge graphs with large language models and other emerging AI technologies.
- Make and document architectural decisions, evaluate technical trade-offs, and define reusable patterns for knowledge graph and AI-enabled applications.
- Collaborate with bioinformaticians, software engineers, product managers, domain experts, and DevOps or platform teams to bring capabilities from prototype to production.
Your profile
- Advanced degree in computer science/ data science/ biostatistics/ related field OR equivalent industry experience. Ideally advanced degree bioinformatics/ computational biology.
- Strong knowledge of knowledge graph design, including schema or ontology modeling, entity resolution, data integration, provenance, and graph querying. Experience with biomedical knowledge graphs is highly desirable. Familiarity with RDF representations and property graph technologies such as Neo4j and Cypher is an advantage.
- Strong Python programming skills for data processing, scientific computing, and application development. Experience with R, Java, or another relevant language is an advantage.
- Experience designing and implementing systems that leverage LLMs, vector databases and agents is a plus.
- Familiarity with computational biology concepts and data types, such as genes, variants, diseases, pathways, molecular interactions, gene expression, functional enrichment, and biological identifiers and ontologies.
- Fluent English with excellent communication skills and an enthusiasm to work in a collaborative, international team environment with an openness to experimentation as well as a passion for exploring new technologies and methodologies.
- This is a hybrid role: 3 days onsite, 2 days from home.
What we offer
Bonus/Commission
Local benefits
Referral Program
Volunteer Day
Internal Academy (QIALearn)
Employee Assistance Program
Hybrid work (conditional to your role)
Our people are the heartbeat of everything we do. Passion drives us as we push boundaries to innovate and evolve. We inspire with our leadership and make an impact with our actions. We cultivate a collaborative, supportive environment where each individual and team can flourish. We champion accountability and encourage entrepreneurial thinking.
QIAGEN is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, or disability.
Skills Required
- Advanced degree in computer science, data science, biostatistics, or a related field, or equivalent industry experience
- Strong knowledge of knowledge graph design, including schema or ontology modeling, entity resolution, data integration, provenance, and graph querying
- Strong Python programming skills for data processing, scientific computing, and application development
- Fluent English and excellent communication skills
- Experience with biomedical knowledge graphs
- Advanced degree in bioinformatics or computational biology
- Familiarity with RDF representations, Neo4j, and Cypher
- Experience with R, Java, or another relevant programming language
- Experience designing systems using large language models, vector databases, and agents
- Familiarity with computational biology concepts and data types, including genes, variants, diseases, pathways, molecular interactions, gene expression, functional enrichment, identifiers, and ontologies
QIAGEN Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about QIAGEN and has not been reviewed or approved by QIAGEN.
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Flexible Benefits — Flexible work options (hybrid or remote where roles allow), flexible hours, sabbaticals, and site-specific childcare support work–life fit. Programs are presented as available where roles allow, signaling adaptable benefit design.
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Wellbeing & Lifestyle Benefits — A global Employee Assistance Program for employees and immediate family, alongside broader wellbeing initiatives and community volunteering time, provides everyday support. Recognition for inclusive culture reinforces the emphasis on a supportive environment.
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Parental & Family Support — Paid parental leave positioned as above typical U.S. norms and family-oriented offerings (e.g., on-site childcare at some locations) enhance caregiver support. Reports of solid PTO and holidays further strengthen family time.
QIAGEN Insights
What We Do
QIAGEN is the leading global provider of Sample to Insight solutions that enable customers to gain valuable molecular insights from samples containing the building blocks of life. Our sample technologies isolate and process DNA, RNA and proteins from blood, tissue and other materials. Assay technologies make these biomolecules visible and ready for analysis. Bioinformatics software and knowledge bases interpret data to report relevant, actionable insights. Automation solutions tie these together in seamless and cost-effective workflows. QIAGEN provides solutions to more than 500,000 customers around the world in Molecular Diagnostics (human healthcare) and Life Sciences (academia, pharma R&D and industrial applications, primarily forensics).
