Brief role description:

• Providing epidemiological insights and evidence to stakeholders across the organisation and external academic partners.
• Guiding study design and analytical methods, ensuring scientific robustness and regulatory relevance.
• Identifying and evaluating optimal data sources, from EMRs and claims databases to clinical trials, and digital health initiatives.
• Collaborating with data scientists to design and deliver analyses that transform data into actionable evidence.
• Communicate findings effectively through reports, presentations, and peer-reviewed publications.
• Contribute to shaping the strategic direction for RWE.

Responsibilities and tasks include:

• Consulting on international RWE projects and large EMA international pilots (e.g., European Health Data Space use case)
• Providing expertise on the prospectively collected administrative and healthcare database studies incl. regulatory assessment of RWE PASS studies
• Leading role on internal taskforce for Danish registry data conversion to common data model (OMOP v5)
• Design, execution and reporting of real-world evidence (RWE) pharmacoepidemiologic studies
• Providing scientific and methodological input on various aspects of study design and conducted or planned analyses
• Writing of study protocols, statistical analysis plans, study reports, scientific manuscripts
• Developing presentations to conferences and stakeholder meetings
• Project management and communication with internal and external stakeholders
• Research student supervision and daily support
• Organisation and planning of a yearly speaker event
• Analytical support of ongoing projects and applied statistical data analyses for regulatory purposes

Responsibilities include:

• Design, execution and reporting of real-world evidence (RWE) pharmacoepidemiologic studies
• Writing of study protocols, statistical analysis plans, study reports, scientific manuscripts
• Providing scientific and methodological input on various aspects of study design and conducted or planned analyses
• Creating abstracts, manuscripts and presentations
• Project management

Skills include:

• Using time-to-event modelling (Cox proportional hazards regression, Fine-Gray subdistribution hazard model), logistic regression, log-binomial regression, propensity-score based adjustment methods
• Teaching incl. epidemiological designs and methods to Masters students overall covering > 200 hours
• Data management, including complex cohort and variables ascertainment from various health and administrative databases, and statistical analyses involving PS adjustment methods (IPTW, ATT weighting, fine PS stratification, PS weighting, PS stratification, PS matching)

Responsibilities include:

• Participating in development of the research protocols and statistical analyses plans for own and collaborative projects
• Independent data management, incl. cohort and variables ascertainment from various Danish health and administrative databases
• Statistical analyses of complex longitudinal health and administrative data