AI Product Manager - ClinicoGenomics
Senior

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BlackCube Labs

Italia

Full Remote

Contratto a tempo indeterminato

Healthcare Technology

Descrizione della Posizione Lavorativa

Join Dedalus, a leading global healthcare technology company, as an AI Product Manager focused on ClinicoGenomics to contribute to safer, more reliable healthcare and have a meaningful professional impact. The role is open to candidates based remotely across European locations; the vacancy is also advertised in Trento, Italy.

As Product Manager - ClinicoGenomics, you will lead the design and delivery of AI-enabled clinical data products that integrate multi-modal information—structured clinical records, genomic datasets and imaging—so as to enable precision medicine workflows within hospitals and health systems.

Key responsibilities include:

  • Define and drive product strategy and roadmap for AI solutions that consolidate and operationalise clinical and genomic data to support precision medicine.
  • Support the Lead Product Manager in maintaining the global AI product roadmap for Health Data, ensuring alignment with corporate strategy and market requirements.
  • Manage the end-to-end lifecycle of assigned products: ideation, requirements, development, launch and iterative improvement.
  • Work directly with healthcare and life-science customers and internal stakeholders to map workflows, identify pain points and uncover opportunities for AI-driven improvements.
  • Build business cases for products, covering scope, costs and ROI.
  • Lead a development team together with a Tech Lead, using agile methodology and ceremonies.
  • Evaluate third-party data platforms, genomics pipelines, AI vendors and precision-medicine toolkits.
  • Define clinical validation frameworks and success metrics for AI-driven precision medicine applications and support sales in market positioning and post-launch monitoring.
  • Collaborate with quality assurance to ensure compliance with regulatory, data protection and clinical safety requirements across target geographies (for example, AI Act, GDPR and HL7/FHIR).
  • Communicate progress, risks and strategic updates to 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 (for example, OMOP and FHIR).
  • Practical experience applying AI/ML to biomedical or clinical data, including familiarity with multimodal data integration challenges.
  • Ability to work across scientific and commercial functions and translate research concepts into product solutions.
  • Excellent communication and stakeholder management skills, with experience interacting with clinical and scientific experts.
  • Native English speaker or equivalent certification (C1/C2).

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.

Benefits

Dedalus states a commitment to diversity, inclusion, equity and equality and promotes a safe, inclusive culture that values diversity and empowers employees to perform at their best.

Requisiti

MSc or PhD in Bioinformatics, Computational Biology, Translational Medical Sciences (or related); minimum 5 years product management experience in healthcare with exposure to clinical and genomic data; practical AI/ML experience on biomedical data; knowledge of OMOP/FHIR; excellent communication and stakeholder management; native English or C1/C2.

Competenze richieste

  • Competenze professionali
  • Product management (healthcare) Genomics Clinical data standards (OMOP FHIR) AI/ML for biomedical data Multimodal data integration Agile development Clinical validation frameworks Regulatory compliance (AI Act GDPR HL7/FHIR) Vendor and platform evaluation Federated data architectures
  • Competenze trasversali
  • Communication Stakeholder management Cross-functional collaboration Leadership Strategic thinking Scientific credibility