Description
As a Statistical Programming Intern at Fortrea, you'll join a global team where curiosity, problem-solving, and analytical thinking are celebrated. You'll gain hands-on experience supporting real clinical trials, work alongside experienced programmers and statisticians, and learn how data drives the delivery of life-changing medicines.
The Statistical Programming Department plays a key role in the clinical development process. Our teams develop, validate, and maintain the programming solutions used to analyze and report clinical trial data. From study start-up through regulatory submission, we deliver accurate and reliable outputs that support scientific and business decision-making.
This internship offers a unique opportunity to develop your programming, analytical, and data interpretation skills within a global, fast-paced environment.
Technical Development: You will gain exposure to tools and SAS language: you will develop and maintain SAS programs to create SDTM and ADaM datasets together with Tables, Figures, and Listings (TFLs).
Cross-Functional Collaboration: Work with global teams, including Biostatistics, Data Management, and Project Management, and experience how different disciplines come together to deliver successful trials.
Real-World Impact: Every dataset, analysis output, and report produced by our Statistical Programming teams contributes to the development of safe and effective therapies. Your work will play an important role in ensuring that clinical data is accurate, reliable, and ready to support regulatory and scientific decision-making.
Education and Qualifications:
- You must be in your second year of a Bachelor's degree in a quantitative or technical field such as Statistics, Mathematics, Computer Science, Data Science, Life Sciences, or another relevant discipline.
- Demonstrated interest in clinical research, statistical programming, or data-driven problem-solving.
- Ability to collaborate effectively with diverse, cross-functional teams.
- Strong organizational and time management skills with attention to detail.
- Proficiency in Microsoft Office, particularly Excel.
- Familiarity with SAS, R, or other statistical software is an advantage but not required.
Other Key Skills:
- Analytical mindset and a passion for working with data.
- Strong communication skills (both written and verbal).
- Curiosity, adaptability, and a proactive approach to learning.
- Ability to manage multiple priorities and meet deadlines.