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Principal Statistical Programmer

Pubblicato il 13-08-2026 - Fortrea in Italia

As a Principal Statistical Programmer in our sponsor-dedicated Flexible Solutions business unit, you are central to the successful delivery of complex projects for a renowned, innovative and global top pharmaceutical company.
You will be involved in liaising with the entire study team as needed, including Clinical, Medical Writing, Safety and Biometrics. It is a great opportunity to see more how this works from a Big Pharma perspective, whilst still being part of a global CRO with opportunity for future career growth.
This position allows you to participate in the development of innovative new benchmark drugs for a wide variety of therapeutic areas.
You can be 100% home-based in EMEA or you can work from our local office in your home country.
Your Responsibilities
- Plan, execute and oversee all programming activities on a study, including but not limited to: resource estimation, working within budget, meeting timelines, maximizing quality, interaction with other departments, etc.
- Oversee SDTM, ADaM and TLF development, perform Senior Review of outputs.




- Liaise with other Sponsor departments for additional programming needs, as required to support publications, medical writing and additional development needs and analyses.
- Support/oversee submission activities (especially in late phase team).
- Ensure all activities are conducted efficiently, with appropriate set-up of needed tools and macros, prioritizing quality at all times.
- Mentor less-experienced team members in best practices around SDTMs, ADaMs and TFLs while ensuring adherence to department standards and processes.

Your Profile
- Ideally, a degree in a relevant field such as mathematics, life sciences, statistics, computer sciences, etc.
- In lieu of the above: professional experience in statistical programming within clinical trials in a biotech, CRO or pharmaceutical company.
- Solid experience with complex clinical trials (minimum 5 years) and the corresponding data sets content (safety and effica

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