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Statistician – Clinical Biostatistics

Smith & Nephew · Coyol

🇬🇧 English
SAS survival analysis regression analysis propensity score analysis sample size calculation statistical modeling study simulation

Descripcion del puesto

About the role

We are looking for a proactive Statistician to join Smith+Nephew’s Global Biostatistics & Data Science team within Global Clinical and Medical Affairs. The role supports the design, analysis and reporting of clinical studies across Advanced Wound Management, Orthopedics and Sports Medicine & ENT portfolios, ensuring robust statistical methodology and reliable results.

Key responsibilities

  • Provide statistical input for study protocols, including sample‑size calculations, randomisation schemes, hybrid and real‑world evidence designs.
  • Develop and execute Statistical Analysis Plans, perform hypothesis testing and generate tables, figures and listings (TFLs) using SAS and R.
  • Conduct comprehensive analyses such as descriptive statistics, survival analysis, regression modelling, subgroup and propensity‑score methods.
  • Perform data review, quality‑control checks and collaborate with data scientists and programmers to clean large real‑world datasets.
  • Prepare and present results to internal teams, regulatory authorities and contribute to Clinical Study Reports and regulatory submissions.
  • Stay current with emerging statistical techniques, industry standards and regulatory guidance for medical‑device studies.

Required profile

  • Strong foundation in clinical biostatistics with experience in medical‑device or pharmaceutical studies.
  • Demonstrated ability to learn continuously and apply innovative statistical solutions.
  • Excellent communication skills for cross‑functional collaboration and regulatory reporting.

Required skills

  • SAS programming
  • R statistical computing
  • Survival and regression analysis
  • Propensity‑score matching, stratification and weighting
  • Sample‑size determination and randomisation design
  • Statistical modelling and study simulation
  • Data quality control and cleaning of large datasets

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Smith & Nephew

Coyol