Lead Statistical Programmer

Lead Statistical Programmer

Pierre Fabre

Haute-Garonne or Hauts-de-Seine, France

Your mission

This position requires a strong expertise in the application of programming within the context of randomized controlled trials (RCTs).

The successful candidate will be agile and adaptable, capable of working in a matrix-organized environment where collaboration across Data Management, Programming, and Statistics is essential. Whilst an excellent track record in Randomized Controlled Trials is a must, the successful candidate will also contribute to Real Worl Evidence (RWE) studies.

Your role within a pioneering company in full expansion

Key Responsibilities

• Participate in the design and execution of RCTs and RWE studies, ensuring high-quality programming support.
• Develop and validate programs for data analysis, reporting, and visualization in accordance with regulatory guidelines and standards (e.g., ICH, EMA, FDA, PMDA).
• Collaborate with statisticians, data managers, and other stakeholders to ensure accurate and efficient data processing and analysis.
• Assist in the selection and evaluation of subcontractors, establishing clear requirements and evaluating proposals.
• Contribute to the preparation of regulatory documents and scientific publications by providing programming support and expertise.
• Follow all industry standards, including ensuring that all biometry-related documentation is included in the electronic Trial Master File (eTMF).

Who you are?

Your skills at the service of innovative projects

• Advanced degree in Statistics (Master's Degree, ENSAI, ISUP, or PhD) or a related field.
• A minimum of 6 years of experience in the pharmaceutical industry or a Contract Research Organization (CRO), with hands-on experience in RCTs and RWE studies.
• Programming in CDISC (SDTM & ADaM) and writing associated documentation (Define, ADRG...)

Mandatory Skills

• Proficiency in SAS and R programming languages
• Extensive experience in Randomized Controlled Trials (RCTs)
• Strong knowledge in CDISC (SDTM & ADaM) and associated documents (Define, ADRG, ...)
• Strong knowledge of international scientific and regulatory recommendations (e.g., ICH, EMA, FDA)
• Ability to collaborate effectively with statisticians, data managers, and other stakeholders
• Excellent written and verbal communication skills in English
• Excellent communication and cooperation skills, with a rigorous and pragmatic approach.
• Creativity, proactivity, rigor, autonomy, and collaborative spirit.
• Strong ability to manage multiple studies simultaneously and maintain organization.

Optional Skills

• Experience with other statistical programming languages (e.g., Python, SQL)
• Knowledge of Real-World Evidence (RWE) studies
• Experience in EMA, FDA or PMDA submissions
• Experience in oncology clinical trials