Biomarker Data Scientist

Join us as we transform immunology and deliver medicines that help autoimmune patients get their lives back. argenx is preparing for multi-dimensional expansion to reach more patients through a rich pipeline of differentiated assets, led by VYVGART, our first-in-class neonatal Fc receptor blocker approved for the treatment of gMG, and with the potential to treat patients across dozens of severe autoimmune diseases. _
- We are building a new kind of biotech company, one that maintains its roots as a science-based start-up and pushes our commitment to innovate across all corners of our business. We strive to inspire and grow our company, our partnerships, our science, and our people, because when we do, we deliver more for patients.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 be the statistical leader for analytical Biomarker strateg ies, analysis for and across autoimmune clinical programs, including support for and reverse translation —spanning early and late development. You’ll advance decision ‑ making through rigorous quantitative methods for Forward and Reverse T ranslational projects, elevate standards for reproducible science across our portfolio and contribute to shape Biomarker -driven study designs.

**What**you’ll**do**
- Own end ‑ to ‑ end Biomarker statistics for autoimmune and immunological disorder trials. Translat e program ‑ critical exploratory research questions into clear, testable quantitative strategies, driv e implementation and evidence ‑ based decision ‑ making ; design and execute robust analyses (e.g., longitudinal models, time ‑ to ‑ event, multiplicity control) ; interpret and report results to drive program decisions, and formulate the findings and impact of the insights to the various stakeholder audiences, in close collaboration with key stakeholders within Quantitative Sciences (QS) and beyond in Clinical, Biomarker and Translational Scientists, and Preclinical Scientists.
- Contribute to data reusab i l ity for meta data analysis and Reverse Translation. Champion reproducible research and traceability best practices; partner with Biomarker Data Management and P rogramming to ensure ALCOA++ compliance and conformance for regulatory interactions, where required.
- Advance data products & visualization. Partner with Biomarker Data Teams to get Biomarker dashboards (R/Shiny, Spotfire, or similar) and tables, lists and figures produced ; promote transparent reporting linked to ADaM, where deemed required.
- Champion modern compute & collaboration. Work in Git ‑ first workflows; leverage cloud data and analytical platforms ( Posit Team for statistical analyses, Databricks for AI/ML, Snowflake for governed analytics) with fit ‑ for ‑ purpose lakehouse /warehouse patterns used widely in life sciences.
- Mentor, influence, and represent. Provide thought leadership in Biomarker analysis and data strategy, collaborate with statistics partners, and contribute to regulatory meetings as needed—consistent with senior biostatistics leadership responsibilities.

**What**you’ll**bring**
- Advanced degree in Biostatistics, Biomedical Science, Bioengineering, or related quantitative field; 8+ pharma/biotech experience spanning clinical development.
- Expert R & Bioconductor (package ecosystem fluency; writing robust, reproducible, tested code); Python for scientific computing and machine learning ; SAS proficiency is valued.
- E xpertise in surrogate markers, diagnostic, prognostic, pharmacodynamic and response predictive biomarker methods is a must ; experience with regulatory strategies utilizing biomarkers a plus
- C ommunicatio n : clear statistical writing, and the ability to translate complex findings for cross ‑ functional teams.
- Deep experience in statistical methods for Biomarker data, including feature engineering, dimensionality reduction, longitudinal modeling, survival analysis, multiplicity adjustment, and robust inference in high ‑ dimensional settings.
- Hands ‑ on experience in machine learning (classification, clustering, regularized models; ideally MLflow ‑ oriented workflows in the cloud), in line with modern Biomarker development.
- Working experience with CDISC standards and submission metadata.
- Data & platform skills: Git, experience with Databricks/Snowflake; familiarity with data engineering patterns for analytics readiness, notion of CI/CD, containerization.
- Dashboarding : R/Shiny, Spotfire, or equivalent.
- On site presence in the Ghent office for 2 days/week.

**Why**argenx**

We dare to do more—together. At argenx you’ll join a global immunology biotech where the science of co ‑ creation drives bold goals and real patient impact. You ’ ll find high ‑ impact over hierarch