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Knowledge Engineer
vor 3 Monaten
The perfect candidate:
The perfect candidate has a University Degree in Data Science / Engineering and at least 3 years of experience of working with data interoperability preferably in the pharmaceutical / medical device environment.
Also expertise in knowledge engineering, software engineering, data modeling, healthcare interoperability, data integration, semantic/graph technologies, data analytics and project management are expected.
We are looking for a motivated and self-driven individual who is ready to come on-site at least one time a week.
General Information:
• Start date: 01.09.2024 (ASAP or latet on 01.10.2024)
• Planned duration: 24 months with further extension planned and intended
• Workplace: Basel
• Workload: 100%
• Remote/Home Office: partial
Background:
The main goal of this project is about developing data technologies, algorithms, models and analytics to enable continuous discovery as well as assess economic value.
The contribution to Diagnostics centers on building and driving the implementation of reusable data products for use by Diagnostics as well as within customer facing software products; establish data architecture to link data products across Diagnostics and beyond; strengthening data skills and mindsets; providing Real World Data and information science expertise to Diagnostics as well as data & analytics across the company.
Tasks & Responsibilities:
- Collaborate with various product teams to shape the development and integration of data models and standardization into the product portfolio and enable FAIR (findable, accessible, interoperable, reusable) data services
- Collaborate with engineering and business teams and co-drive projects to implement interoperability standards for devices and digital products adhering to FAIR principles
- Investigate innovative methods to generate new business insights from interlinked data sources (lab and clinical) that may mature into new features of digital products
- Drive the adoption and integration of interoperability standards including terminological resources (e.g. FHIR, HL7v2, LOINC, SNOMED) for RIS digital products
- Engage with internal key customers and stakeholders to understand their business needs, pain points using a customer-centric approach
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