Lead Biostatistician - Clinical Trials Leadership

Lead Biostatistician - Clinical Trials Leadership

Full-Time 60000 - 75000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead statistical strategy for clinical trials and ensure data quality.
  • Company: Join ePharmIT, a leader in innovative clinical trial solutions.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and excellence.
  • Why this job: Make a real impact in healthcare by leading groundbreaking research.
  • Qualifications: MS or PhD in statistics/biostatistics with clinical trial experience.

The predicted salary is between 60000 - 75000 Β£ per year.

e Pharm IT seeks a Principal Biostatistician to lead statistical strategy on bronchiectasis or hepatitis B programs.

You will develop protocols, study designs, and SAPs while providing statistical oversight to ensure data quality and analysis integrity.

Candidates should hold an MS or Ph D in statistics/biostatistics, with expertise in Poisson regression, time-to-event and multiple imputation, and industry experience in clinical trials.

Excellent communication skills are essential.

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Lead Biostatistician - Clinical Trials Leadership employer: ePharmIT

As a Principal Biostatistician, you will thrive in a dynamic and supportive work environment that prioritises employee growth and development. Our company offers competitive benefits, a collaborative culture, and opportunities to engage in impactful research within the fields of Bronchiectasis and Hepatitis B. Located in a vibrant area, we provide a unique advantage for professionals seeking meaningful and rewarding employment in the biostatistics domain.

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Contact Details:

ePharmIT Recruitment Team

We think you need these skills to ace Lead Biostatistician - Clinical Trials Leadership

Statistical Strategy Development
Protocol Development
Study Design
Statistical Analysis Plans (SAPs)
Data Quality Assurance
Poisson Regression
Time-to-Event Analysis