Senior Statistical Programmer: Shape Global Submissions

Bristol-Myers Squibb; Uxbridge; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Bristol Myers Squibb in the UK is seeking a Senior Statistical Programmer to drive programming work within our Global Biometrics & Data Sciences function, collaborating with cross-functional clinical teams and external vendors. This role offers autonomy, high-impact projects, and exposure to regulatory submissions; you will produce SDTM/ADaM datasets, TFLs, and contribute to NDA/BLA/MAA processes.

You will own programming assignments across projects with minimal supervision and shape study

Qualifications

• Hands-on SAS programming to generate derived analysis datasets and TFLs.
• In-depth understanding of clinical data structures and SDTM/ADaM standards.
• Experience supporting regulatory submissions (NDA/BLA/MAA) is a plus.
• Familiarity with data presentation and regulatory expectations.

Responsibilities

• Write and validate SAS programs to create derived analysis datasets and TFLs.
• Contribute to electronic submissions (NDA/BLA/MAA) and regulatory milestones.
• Review SAPs and Data Presentation Plans before programming work begins.
• Collaborate with vendors on programming standards and file transfers.
• Lead programming assignments across multiple projects with minimal supervision.

Skills

SAS programming

SDTM/ADaM

Regulatory submissions

Cross-functional collaboration

Data handling & analytics

Education

Bachelor's in Statistics/Biostatistics/Mathematics/Computer Science/Life Sciences

Tools

Pinnacle 21

MS Office

XML

Job description

Bristol Myers Squibb in the UK is seeking a Senior Statistical Programmer to drive programming work within our Global Biometrics & Data Sciences function, collaborating with cross-functional clinical teams and external vendors. This role offers autonomy, high-impact projects, and exposure to regulatory submissions; you will produce SDTM/ADaM datasets, TFLs, and contribute to NDA/BLA/MAA processes.

You will own programming assignments across projects with minimal supervision and shape study