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Biomarker data scientist

Gand
Data Scientist
Publiée le 20 janvier
Description de l'offre

Atargenx,we’reall 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 foranalyticalBiomarkerstrategies,analysisfor andacross autoimmune clinical programs, including support forand reverse translation—spanning early and late development.You’lladvance decision‑makingthroughrigorous quantitative methodsfor Forward and ReverseTranslational projects, elevate standards for reproducible science across our portfolioand contribute toshapeBiomarker-drivenstudydesigns.

Whatyou’lldo

1. Own end‑to‑endBiomarkerstatistics for autoimmuneand immunological disordertrials.Translateprogram‑criticalexploratory researchquestions into clear, testable quantitative strategies,driveimplementation and evidence‑based decision‑making; designand executerobust analyses (e.g., longitudinal models, time‑to‑event, multiplicity control);interpretand reportresults to drive program decisions,and formulate the findingsand impact of the insightsto the various stakeholderaudiences,in close collaboration with key stakeholders within Quantitative Sciences (QS)andbeyondin Clinical,Biomarkerand TranslationalScientists,and Preclinical Scientists.

2. Leadinnovativeanalysis ofBiomarkerand multi‑omics data. Apply rigorous methods for high‑dimensional datasets (transcriptomics/proteomics/metabolomics); integrate across modalities; define robust QC/normalization strategies.

3. Apply andelevateinternal Data Scienceexcellence. Set standards for reproducibledata analysis workflowsandpackage ecosystems; mentor teams in advanced R practices for bioinformatics.

4. Contribute to datareusabilityfor metadata analysis and Reverse Translation.Championreproducible researchand traceability best practices; partner withBiomarker Data Management andProgramming toensure ALCOA++ compliance andconformance for regulatory interactions, whererequired.

5. Advance data products & visualization. Partner withBiomarkerData TeamstogetBiomarkerdashboards (R/Shiny, Spotfire,or similar) andtables, lists and figuresproduced; promote transparent reporting linked toADaM, wheredeemedrequired.

6. Champion moderncompute& collaboration. Work in Git‑first workflows; leverage cloud dataand analyticalplatforms (Posit Team for statistical analyses,Databricks for AI/ML, Snowflake for governed analytics) with fit‑for‑purposelakehouse/warehouse patterns used widely in life sciences.

7. Mentor, influence, and represent. Provide thought leadership inBiomarkeranalysis and datastrategy, collaborate withstatisticspartners, and contribute to regulatory meetings as needed—consistent with senior biostatistics leadership responsibilities.

Whatyou’llbring

8. Advanced degree in Biostatistics, Biomedical Science, Bioengineering, or related quantitative field;8+pharma/biotech experience spanning clinical development.

9. Expert R&Bioconductor (package ecosystem fluency; writing robust,reproducible,tested code); Python for scientific computingand machine learning; SASproficiencyis valued.

10. Expertisein surrogate markers,diagnostic, prognostic, pharmacodynamic and responsepredictive biomarker methods isa must; experience with regulatory strategiesutilizingbiomarkers a plus

11. Communication: clear statistical writing, and the ability to translate complex findings for cross‑functional teams.

12. Deep experience in statistical methods forBiomarkerdata, including feature engineering, dimensionality reduction, longitudinal modeling, survival analysis, multiplicity adjustment, and robust inference in high‑dimensional settings.

13. Hands‑onexperience inmachine learning (classification, clustering, regularized models; ideallyMLflow‑oriented workflows in the cloud), in line with modernBiomarkerdevelopment.

14. Working experience with CDISC standards andsubmissionmetadata.

15. Data & platform skills: Git, experience with Databricks/Snowflake; familiarity with data engineering patterns for analytics readiness, notion ofCI/CD, containerization.

16. Dashboarding:R/Shiny,Spotfire,or equivalent.

17. On site presence in the Ghent office for 2 days/week.

Whyargenx

We dare to do more—together. Atargenxyou’lljoin a global immunology biotech where the science of co‑creation drives bold goals and real patient impact. You’llfind high‑impact over hierarchy, and a culture where Argonauts collaborate across borders to turn precision science into medicines.

Offer

18. Member of a cross-disciplinary team involved in clinical development of therapeutic antibodies.

19. Opportunity to contribute to the continued build-out of the TranslationalDataScience team.

20. Competitive salary package with extensive benefits.

Apply

Your application and related information will remain strictly confidential.

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