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Not Specified Permanent

Morristown, New Jersey · USA job

Senior Principal Statistician, Biometrics

Ferring

Morristown, New Jersey

This job is no longer available — it was removed from the JobsMint Pro catalog and cannot be applied to. Location: Morristown, New Jersey · 07960

Job description

Overview

As a Senior Principal Statistician in Biometrics, you will contribute to design, analysis, and reporting within clinical development and evidence generation programs. You will blend clinical trial data with real-world evidence to inform regulatory decisions and lifecycle strategies. You'll work across integrated evidence generation efforts, supporting regulatory submissions and HTA inputs. This role offers impact on program design and asset value through rigorous statistical methodology and collaboration with cross-functional teams.

Compensation / Benefits
  • competitive total compensation
  • flexible benefits
  • comprehensive healthcare
  • 401k with company match
  • paid parental leave
  • tuition reimbursement
Responsibilities
  • Design, conduct, analyze and report RWE studies; contribute to integrated evidence generation strategies
  • Provide statistical input to clinical development plans and target product profiles
  • Author statistical analysis plans and contribute to study design
  • Analyze and interpret clinical trial data; contribute to clinical study reports and regulatory submissions
  • Assess business development opportunities and support due diligence with statistical rigor
  • Conduct gap analyses to identify missing data and design further studies or registries
  • Perform independent analyses of endpoints, subgroups, and sensitivity analyses to validate asset potential
  • Review analysis plans and submission documentation to inform regulatory decisions
Key requirements
  • Bachelor's degree; Master's or PhD in Statistics/ Biostatistics or related field preferred
  • 5+ years in the pharmaceutical industry
  • Proficiency in R and SAS
  • Experience with registry/claims data and observational data methods (synthetic/external controls, target trial emulation, causal inference)
  • Strong analytical thinking and ability to translate data into insights
  • Effective communication and collaborative skills in a dynamic environment
  • effective communication
  • collaborative mindset
  • strong analytical thinking
  • R
  • SAS
  • observational data methodologies (synthetic/external controls, target trial emulation)

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