Real World Biostatistician – RWA CMH Experience

🕒 September 10

🌐 Canada, United States – Remote

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⏰ Full Time

🟡 Mid-level

🟠 Senior

🧪 Clinical Research

👻 Ghost score 10%

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Syneos Health

10,000+ employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Syneos Health is a leading fully integrated biopharmaceutical solutions organization built to accelerate customer success. They translate unique clinical, medical affairs, and commercial insights into outcomes to address modern market realities. By utilizing advanced technologies and insights, Syneos Health collaborates with clients to speed the delivery of important therapies to patients worldwide, offering services that span the entire clinical-to-commercial spectrum.

📋 Description

• Design and execute real-world evidence studies using EMR and claims data • Conduct data specifications, statistical analysis plans, and protocols with key research objectives • Develop and apply robust statistical methodologies, including causal inference methods, GLM/GLMM, MMRM, survival analysis, and random forest • Apply trial emulation frameworks • Develop external control arms and borrowing strategies • Perform data analysis using healthcare coding systems such as ICD and NDC • Conduct sample size estimation and power calculations for observational and hybrid study designs • Collaborate with HEOR, Market Access, Regulatory, and Clinical Development stakeholders • Translate complex analytical results into clear, actionable insights through PowerPoint or study reports • Support methodological innovation in real-world evidence, including machine learning integration where appropriate

🎯 Requirements

• M.S. or Ph.D. in Biostatistics, Statistics, Epidemiology, or related field • ≥5 years of experience in RWA/RWD analytics (industry or equivalent) • Strong experience with EMR and/or claims data • Proficiency in healthcare coding systems (e.g., ICD, NDC) • Programming expertise in at least one of: SAS, R, or Python • Working knowledge with SQL logic and OMOP data structures • Solid understanding of causal inference methods • Solid understanding of observational study design • Solid understanding of sample size and power considerations • Ability to independently write cohort definitions in SQL logic • Ability to debug data issues, including time zero alignment and exposure gaps • Understanding of concept mapping (ICD ↔ SNOMED ↔ RxNorm) • Ability to translate statistical estimands into censoring rules and data extraction logic • RWE CMH experience • Equivalent experience, skills, and/or education may be considered

🏖️ Benefits

• Career development and progression • Supportive and engaged line management • Technical and therapeutic area training • Peer recognition • Total rewards program • Inclusive culture • Reasonable accommodations when appropriate

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