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- Tasks: Lead and support clinical trials using advanced SAS programming and CDISC standards.
- Company: Innovative pharmaceutical company focused on data-driven solutions.
- Benefits: Fully remote work, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in healthcare by analysing clinical trial data.
- Qualifications: 8+ years of SAS programming experience and strong analytical skills.
- Other info: Join a diverse team that values collaboration and innovation.
The predicted salary is between 36000 - 60000 £ per year.
As a Senior Statistical Programmer, you will leverage your advanced SAS programming skills and proficiency in CDISC standards (SDTM & ADaM) to support or lead one or more Phase I-IV clinical trials. This role can be performed as fully remote.
Responsibilities
- Performing data manipulation, analysis and reporting of clinical trial data, both safety and efficacy (ISS/ISE), utilizing SAS programming
- Generating and validating SDTM and ADaM datasets/analysis files, and tables, listings, and figures (TLFs)
- Production and QC / validation programming
- Generating complex ad-hoc reports utilizing raw data
- Applying strong understanding/experience of Efficacy analysis
- Creating and reviewing submission documents and eCRTs
- Communicating with and/or responding to internal cross-functional teams and client for project specifications, status, issues or inquiries
- Performing lead duties when called upon
- Serving as team player, with a willingness to go the extra distance to get results, meet deadlines, etc.
- Being adaptable and flexible when priorities change
Qualifications
- Bachelor’s degree in Statistics, Computer Science, Mathematics, or related field
- At least 8 years of SAS programming experience with clinical trial data in the Pharmaceutical & Biotech industry with a bachelor’s degree or equivalent; at least 6 years of related experience with a master’s degree or above
- Study lead experience, preferably juggling multiple projects simultaneously
- Strong SAS data manipulation, analysis and reporting skills
- Solid experience implementing the latest CDISC SDTM / ADaM standards
- Strong QC / validation skills
- Good ad-hoc reporting skills
- Proficiency in Efficacy analysis
- Familiarity with drug development life cycle and experience with the manipulation, analysis and reporting of clinical trials’ data
- Submissions experience utilizing define.xml and other submission documents
- Experience supporting immunology, respiratory or oncology studies would be a plus
- Excellent analytical & troubleshooting skills
- Ability to provide quality output and deliverables, in adherence with challenging timelines
- Ability to work effectively and successfully in a globally dispersed team environment with cross-cultural partners
Senior Statistical Programmer FSP employer: Cytel - EMEA
Contact Detail:
Cytel - EMEA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Statistical Programmer FSP
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend relevant webinars, and join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions related to SAS programming and clinical trials. We recommend doing mock interviews with friends or using online platforms to get comfortable with articulating your experience.
✨Tip Number 3
Showcase your skills through a portfolio! If you’ve worked on interesting projects or analyses, compile them into a portfolio to share during interviews. This gives potential employers a tangible sense of what you can bring to the table.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Statistical Programmer FSP
Some tips for your application 🫡
Show Off Your SAS Skills: Make sure to highlight your advanced SAS programming skills in your application. We want to see how you've used these skills in real-world scenarios, especially in clinical trials. Don't hold back on the details!
CDISC Standards are Key: Since we're all about CDISC standards like SDTM and ADaM, be sure to mention your experience with these in your application. We love seeing candidates who can demonstrate their understanding and application of these standards.
Tailor Your Application: Take a moment to tailor your application to our values and the job description. We appreciate when candidates show they understand our mission and how they can contribute to our team. It makes a big difference!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you're keen to join our team!
How to prepare for a job interview at Cytel - EMEA
✨Master the Technical Skills
Make sure you brush up on your SAS programming skills and CDISC standards, especially SDTM and ADaM. Be ready to discuss specific projects where you've applied these skills, as this will show your practical experience and understanding of the role.
✨Showcase Your Problem-Solving Abilities
Prepare examples of how you've tackled complex data manipulation or analysis challenges in previous roles. Highlight your analytical and troubleshooting skills, as these are crucial for a Senior Statistical Programmer.
✨Demonstrate Team Collaboration
Since this role involves working with cross-functional teams, be prepared to share experiences where you've successfully collaborated with others. Emphasise your adaptability and willingness to go the extra mile to meet deadlines.
✨Familiarise Yourself with the Drug Development Life Cycle
Understanding the drug development process is key. Brush up on your knowledge of clinical trials and be ready to discuss how your experience aligns with the phases of drug development, particularly in relation to efficacy analysis.