Biomarker Biostatistics Lead

At argenx, we’re all in on our innovation mission to transform care for people living with severe autoimmune diseases. We speak the language of science, put patients first, and value high‑impact over hierarchy. If you’re energized by bold ideas and collaborative problem‑solving—patients are waiting. 

The opportunity 

You will serve as a Biomarker Biostatistics Lead supporting autoimmune clinical development programs from early to late phase, including translational and reversetranslational activities. In this role, you will provide scientific and statistical leadership for biomarker strategies, ensuring that analyses are methodologically sound, interpretable, and aligned with clinical questions and development objectives. You will contribute to biomarkerdriven study designs, integrated clinical–biomarker analyses and evidence generation, and the advancement of reproducible quantitative practices across the portfolio. 

What you’ll do 

• Lead biomarker biostatistics across clinical development programs. Translate clinical and translational questions into welldefined statistical objectives; design, justify, and execute robust analyses (e.g. longitudinal and repeatedmeasures models, timetoevent analyses, multiplicity control); interpret results in the context of clinical relevance and program decisionmaking.  

• Act as the primary statistical partner for Clinical, Biomarker, and Translational teams on biomarkerrelated topics, contributing to experimental design, biomarker sampling strategies, statistical sections of biomarker documents, and integrated analysis and interpretation of clinical and biomarker data.  

• Provide statistical oversight of exploratory and translational biomarker analyses, including single, complex and highdimensional datasets, ensuring appropriate QC, normalization, sensitivity analyses, and transparent reporting.  

• Support biomarker utility assessment (e.g. exploratory, pharmacodynamic, prognostic, predictive) and contribute to discussions on biomarker qualification, interpretation, and readiness for clinical or regulatory use where applicable.  

• Ensure reproducibility, traceability, and data integrity of biomarker analyses in collaboration with Biomarker Data Management and Statistical Programming, aligned with ALCOA++ principles and regulatory expectations.  

• Contribute to clear and consistent reporting through highquality tables, listings, figures, and welldocumented dashboards that support governance, clinical interpretation, and crossstudy learning.  

• Mentor and influence, promoting sound statistical reasoning, best practices in Rbased analysis, and consistency in biomarker analysis approaches across programs.  

• Represent biomarker biostatistics in crossfunctional, governance, and (as appropriate) regulatory interactions, consistent with senior biostatistics leadership responsibilities. 

What you’ll bring 

• Advanced degree in Biostatistics, Statistics, or a closely related quantitative discipline; 8+ years of experience in pharma or biotech, with a strong focus on clinical development.  

• Deep expertise in statistical methods for clinical and biomarker data, including longitudinal modeling, survival analysis, multiplicity adjustment, and robust inference across diverse biomarker endpoints.  

• Proven experience with diagnostic, pharmacodynamic, prognostic, predictive, and/or surrogate biomarkers, ideally within autoimmune or immunology programs; experience supporting regulatory biomarker strategy is a plus.  

• High proficiency in R for statistical analysis, reporting, and reproducible workflows; familiarity with Bioconductor or other biomarkerrelevant packages is valued. Python and/or SAS experience is an advantage.  

• Strong ability to clearly communicate statistical concepts and results to nonstatisticians and senior decisionmakers, both in writing and in discussion.  

• Experience working with CDISC standards (SDTM/ADaM) and contributing to submissionready or inspectionready analyses.  

• Experience with versioncontrolled, collaborative analysis environments (e.g. Gitbased workflows) and good documentation practices.  

• Experience with data visualization or dashboarding (e.g. R/Shiny, Spotfire, or similar) to support clinical interpretation.  

• Onsite presence in the Ghent office for 2 days per week.