Statistical Programmer
Listed on 2026-10-13
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IT/Tech
Data Scientist, Data Analyst, Data Engineering, Data Science Manager
We are seeking motivated Entry-Level Statistical Programmers to join our biometrics team. These positions are ideal for recent graduates with a Master's degree (preferred) and strong programming skills in Statistics, Mathematics, Computer Science, Data Science, Analytics, Engineering, or related quantitative disciplines.
The successful candidates will receive comprehensive training in clinical trial programming, CDISC standards, and regulatory submission requirements while working with experienced statisticians and programmers.
We are particularly interested in candidates who are passionate about programming and have developed strong SAS and R programming skills through academic research, internships, capstone projects, or industry experience.
We would like the candidate to be on-site for 1st one year and can be hybrid or remote after 1 year.
Key Responsibilities- Develop and validate statistical programs using SAS and R.
- Support creation of SDTM and ADaM datasets.
- Generate tables, listings, and figures (TLFs).
- Perform programming quality control and validation.
- Review/Create specifications and study documentation.
- Contribute to automation, reusable tools, and process improvement initiatives.
- Collaborate with statisticians, data managers, and clinical teams.
- Master's degree preferred;
Bachelor's and PhD degrees considered. - Degree in Statistics, Mathematics, Computer Science, Data Science, Analytics, Engineering, or a related quantitative field.
- SAS programming certificates are a strong plus
- Demonstrated passion for programming and software development.
- Extensive hands-on experience using SAS and R through coursework, research, internships, or personal projects.
- Strong analytical and problem-solving skills.
- Excellent attention to detail.
- Strong written and verbal communication skills.
- Experience with Python, SQL, or other programming languages.
- Experience with Git, version control, or software development practices.
- Knowledge of machine learning, AI tools, or data automation.
- Interest in pharmaceutical, biotech, or healthcare applications.
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