Lead Statistical Programmer – Clinical Trials (SAS & R)

ICON; Warszawa; On-site; PLN 180,000 - 260,000; Full time

Job summary

ICON plc is actively seeking a Study Lead Programmer in Warsaw to lead statistical programming tasks for clinical trial data analysis and reporting. You will develop and validate programs using SAS and R, collaborating with biostatisticians to define analysis plans and ensure high-quality results.

You will also perform QC on outputs, contribute to regulatory submissions, and drive process improvements in programming practices within a global healthcare research environment.

Qualifications

• Bachelor's degree in statistics, computer science, mathematics or related discipline.
• Experience in statistical programming in clinical research or pharmaceutical settings.
• Strong proficiency in SAS and R.
• Excellent analytical and problem-solving skills.
• Strong communication skills and ability to work collaboratively.

Responsibilities

• Developing and validating programs for statistical analysis and reporting of clinical trial data using SAS and R.
• Collaborating with biostatisticians to define analysis plans and statistical methods.
• Performing quality control checks on statistical outputs and ensuring accuracy in reporting.
• Assisting in preparation of statistical reports for regulatory submissions.
• Contributing to process improvements in programming practices.

Skills

Statistical programming

Analytical thinking

Problem solving

Communication

Teamwork

Education

Bachelor's degree in statistics, computer science, mathematics or related

Tools

SAS

R

Job description

ICON plc is actively seeking a Study Lead Programmer in Warsaw to lead statistical programming tasks for clinical trial data analysis and reporting. You will develop and validate programs using SAS and R, collaborating with biostatisticians to define analysis plans and ensure high-quality results.

You will also perform QC on outputs, contribute to regulatory submissions, and drive process improvements in programming practices within a global healthcare research environment.