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Evidence Manager (Hybrid)

novartis · Taipei

New
Hybrid Senior 🇬🇧 English
SAS S-Plus EMR Study design Protocol writing

Job description

About the role

Novartis Taiwan is looking for an Evidence Manager in Taipei, working in a hybrid setting. The role translates global evidence strategies into local impact for patients, healthcare professionals and the wider healthcare ecosystem, shaping evidence generation in Taiwan while collaborating with local and global teams.

Key responsibilities

  • Adapt Global Integrated Evidence Plans to the Taiwan market, aligning them with local regulatory, access, reimbursement and clinical practice needs.
  • Identify and prioritise local evidence gaps from stakeholder insights, product strategy and healthcare priorities.
  • Translate the evidence strategy into actionable Local Evidence Plans, working with cross-functional teams.
  • Lead local clinical studies and real-world evidence activities across the full lifecycle, from design and execution to analysis, interpretation and communication of results.
  • Build and strengthen collaborations with medical experts, investigators, academic institutions and data partners.
  • Integrate external insights into evidence strategy and study design, and promote advanced RWD methodologies and novel study designs.
  • Align with Global Medical Affairs evidence generation strategies, processes, governance and compliance expectations.

Required profile

  • Advanced degree in Life Sciences, Epidemiology, Biostatistics or a related field.
  • Minimum 3 years of RWE experience using healthcare databases or EMRs, in industry, consulting or CRO settings.
  • Strong expertise in study design, protocol writing, statistical methodology and evidence generation execution.
  • Relevant medical or clinical background, with strong communication and interpersonal skills.
  • Fluent written and spoken English and Mandarin.

Required skills

  • Analytical tools such as SAS, R, S-Plus or other business or research analytics software.
  • Understanding of multivariable models (Cox, Poisson, binomial and multinomial logistic models, ANOVA, MANOVA, cluster, discriminant and factor analysis).

Questions fréquentes

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Source : ats:workday

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Published 1天前

Expires 1个月后

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novartis

Taipei