Descrizione della Posizione Lavorativa
Do you want meaningful work that improves healthcare? Join Dedalus as an AI Product Manager - ClinicoGenomics and help make care safer, more reliable and better across health systems. The role can be performed remotely from any of our European locations.
In this position you will lead the creation of AI-enabled clinical data products focused on the consolidation and analysis of multi-modal clinical data — including structured clinical records and genomic information — and apply advanced AI to enable precision medicine workflows in hospitals and health systems.
The ideal person will combine strong scientific credentials with product experience: able to converse credibly with clinical and research stakeholders and to turn complex multi-omics and imaging use cases into commercially viable AI solutions.
Key responsibilities
- Define and drive product strategy and roadmap for AI applications that operationalise clinical and genomic data to support precision medicine workflows.
- Support the Lead Product Manager in maintaining the global AI product roadmap for Health Data and aligning it with corporate strategy and market needs.
- Manage the end-to-end lifecycle of assigned products from ideation and requirements gathering through launch and iterative improvement.
- Engage directly with healthcare and life-science customers and internal teams to understand workflows, pain points and opportunities for AI-driven improvements.
- Create business cases for products, including scope, cost and ROI assessments.
- Lead a development team in partnership with a Tech Lead using agile methodologies and ceremonies.
- Evaluate third-party data platforms, genomics pipelines, AI vendors and precision medicine toolkits relevant to the portfolio.
- Define clinical validation frameworks and success metrics for AI-driven precision medicine applications and support sales in positioning, adoption monitoring and impact assessment post-launch.
- Collaborate with quality assurance to ensure compliance with applicable regulatory, data privacy and clinical safety requirements across target geographies (for example the AI Act, GDPR and HL7/FHIR standards).
- Communicate progress, risks and strategic updates to relevant stakeholders.
Essential requirements
- Advanced degree (MSc or PhD) in Bioinformatics, Computational Biology, Translational Medical Sciences or a closely related field.
- Minimum 5 years of product management experience in a healthcare context, with direct exposure to clinical and genomic data environments.
- Proven understanding of genomics and clinical data standards (e.g. OMOP, FHIR).
- Practical experience applying AI/ML to biomedical or clinical data and familiarity with multimodal data integration challenges.
- Strong ability to work across scientific and commercial functions to translate research concepts into products.
- Excellent communication and stakeholder management skills and experience engaging clinical and scientific experts.
- Native English speaker or C1/C2 level English certification.
Desirable
- Experience at or with AI-native companies and iterative, data-driven development practices.
- Knowledge of precision oncology, rare-disease diagnostics or pharmacogenomics use cases.
- Familiarity with federated data architectures, de-identification frameworks or synthetic data for clinical AI development.
Application closing date: 31st May 2026.
Dedalus is committed to diversity, inclusion, equity and equality and aims to create a safe, inclusive culture that celebrates diversity in all forms and empowers everyone to be their best.
Requisiti
MSc or PhD in Bioinformatics/Computational Biology/Translational Medicine or related; minimum 5 years product management experience in healthcare with exposure to clinical and genomic data; understanding of genomics and standards (OMOP, FHIR); practical AI/ML experience on biomedical data; strong cross-functional collaboration and stakeholder communication; native English or C1/C2 certification.
Competenze richieste
Competenze professionali
Genomics
Clinical data standards (OMOP
FHIR)
AI/ML for biomedical data
Multimodal data integration
Product lifecycle management
Agile methodologies
Regulatory and data privacy knowledge (GDPR
AI Act
HL7/FHIR)
Competenze trasversali
Stakeholder management
Cross-functional collaboration
Communication
Leadership
Strategic thinking