Senior Statistical Programmer II
AstraZeneca (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 14–25 LPA
Posted on 11 Sept
Reach people at AstraZeneca
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at AstraZeneca you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Provide statistical programming support and/or lead programming activities related to analysis and reporting at project/study level in Oncology clinical development.
- Deliver statistical programming components for clinical study reports, regulatory submissions, commercialization, and scientific data use for AstraZeneca products.
- Lead studies or activities including stakeholder management within the Oncology therapeutic area, ensuring compliance with technical and regulatory requirements.
Minimum Requirements
- Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, Life or Social Sciences, or related field.
- At least 3 years industry experience with a Master’s degree or 5+ years with a Bachelor’s degree in relevant domain.
- Advanced expertise in SAS programming within clinical drug development.
- Experience leading studies or activities in clinical trials, with knowledge of CDISC standards and regulatory requirements in pharma programming.
Ideal Candidate Profile
- Demonstrated ability to lead and manage programming activities in Oncology clinical trials and submissions.
- Strong stakeholder management experience in Oncology therapeutic area with regulatory submission exposure.
- Capable of working independently and multitasking across concurrent studies in a global team environment with detailed focus.