At a Glance
- Tasks: Write and validate SAS/R programs, produce TFLs, and support clinical trial submissions.
- Company: Join Bristol Myers Squibb, a leader in the pharmaceutical industry.
- Benefits: Enjoy hybrid work, competitive salary, and opportunities for professional growth.
- Other info: Work in a dynamic environment with excellent career advancement opportunities.
- Why this job: Make a real impact in clinical trials while working with cutting-edge statistical programming.
- Qualifications: 2+ years of experience in SAS, CDISC knowledge, and team collaboration skills.
The predicted salary is between 63000 - 77000 £ per year.
Bristol Myers Squibb in Uxbridge is seeking a Statistical Programmer to join GBDS.
You will write and validate SAS/R programs, produce TFLs, and support regulatory submissions across clinical trials.
The role involves hybrid work, with 50% onsite in our Uxbridge office.
The candidate brings 2+ years of experience, SAS expertise, CDISC knowledge, and familiarity with SDTM/ADa M. Collaboration with project teams and external partners is essential.
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Statistical Programmer – Hybrid UK (SAS/ADaM) in Uxbridge employer: Bristol Myers Squibb
Bristol-Myers Squibb in Uxbridge is an exceptional employer, offering a dynamic work culture that prioritises collaboration and innovation. Employees benefit from extensive career growth opportunities, mentorship programs, and the chance to contribute meaningfully to life-changing clinical trials, all while enjoying a supportive environment that values data integrity and compliance.
StudySmarter Expert Advice🤫
We think this is how you could land Statistical Programmer – Hybrid UK (SAS/ADaM) in Uxbridge
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We think you need these skills to ace Statistical Programmer – Hybrid UK (SAS/ADaM) in Uxbridge
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
