RWE Biostatistician

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🔥 0 minutes ago

🇫🇷 France – Remote

⏰ Full Time

🟢 Junior

🟡 Mid-level

🧪 Clinical Research

🚫👨‍🎓 No degree required

👻 Ghost score 10%

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Resilience

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2020

🏭 Manufacturing

🏥 Healthcare

📦 Logistics

Manufacturing • Healthcare • Logistics

Resilience is a leading biomanufacturing innovation company focused on the development of novel medicines. Specializing in the manufacturing of complex medicines such as cell and gene therapies, Resilience partners with small and mid-sized biotech firms to provide customized solutions that leverage cutting-edge technologies and scientific advancement. Their approach includes high-tech, end-to-end drug substance and drug product manufacturing capabilities aimed at ensuring rapid, safe, and scalable production. Resilience operates primarily in North America, with expertise in delivering regulatory-compliant solutions across global markets, enhancing the reliability and accessibility of biopharmaceutical supply chains.

📋 Description

• Draft and/or contribute to Statistical Analysis Plans (SAP) and methodological documentation • Program analyses in R and Python, with SQL/PostgreSQL concepts • Contribute to Real-World Evidence (RWE) studies through design, methods, and execution • Set up data quality checks, including consistency and cohort rules, and document assumptions • Produce decision-ready deliverables such as tables, figures, and reporting • Explain results to non-statisticians, including internal and external stakeholders • Support more reliable, faster, and reproducible study execution across plans, code, and reporting • Enable cross-functional teams to make informed decisions

🎯 Requirements

• 2–4 years of experience in biostatistics/RWE (CRO, consultancy or similar environments) • Experience delivering analyses on healthcare datasets • Experience building reusable outputs, including codebases, pipelines, and reporting templates • Experience working closely with non-technical stakeholders • Ability to apply biostatistics, including survival analysis (Kaplan-Meier, log-rank, Cox), regression, GLM/GLMM, and matching/weighting • Ability to write clean, reproducible code in R and Python, with basic SQL/PostgreSQL knowledge • Experience working with patient healthcare data, including quality, traceability, and constraints • Ability to produce clear statistical and methodological documentation, including protocols, SAPs, and reports • Ability to build meaningful data visualisations • High methodological rigor and attention to detail • Autonomy and ownership mindset • Ability to prioritize and handle multiple studies in parallel • Clear communication and collaborative approach • Plus: knowledge of GxP and ICH E9/E9(R1) good practices • Plus: exposure to machine learning applied to healthcare data • Plus: experience with external vendors such as Pharma and CROs

🏖️ Benefits

• High-impact healthcare mission at the intersection of care, data and clinical research • Broad scope: RWE, Medical Affairs studies, standardisation and automation