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- Tasks: Transform real-world study data into CDISC-compliant datasets using R.
- Company: Join a leading research team focused on innovative health projects.
- Benefits: Competitive pay, flexible hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on quality and reproducibility.
- Why this job: Make a real impact in healthcare by working on exciting projects.
- Qualifications: Experience with CDISC standards and strong R programming skills required.
The predicted salary is between 40000 - 50000 £ per year.
Our client is seeking an experienced Statistical Programmer as a full time contractor for 6 months. The successful candidate will work closely with the Head of Statistics, an existing Statistical Programmer, and the wider research team to deliver on an exciting new project looking at the disease course of Atrial Fibrillation. The primary focus of the role is to support the creation of CDISC-compliant datasets, primarily SDTM and, where needed, ADaM, for an observational real-world study. The successful candidate will be expected to develop programming solutions and dataset specifications in R, based on the protocol, eCRF, and study requirements.
Key Responsibilities
- Lead the conversion of raw observational study data into CDISC SDTM datasets and drive the end-to-end development of ADaM datasets.
- Develop R code to transform source data into standardised structures.
- Review the study protocol, annotated CRF/eCRF, and related documentation to identify dataset and metadata requirements.
- Write trial design datasets/specifications, SDTM specifications, and ADaM specifications.
- Translate EDC/eCRF structures into detailed SDTM mapping specifications, including derivation and transformation logic.
- Prepare and maintain key submission-supporting documents, including: SDTM Review Guide, ADaM Review Guide, define.xml, controlled terminology / codelist documentation.
- Validate datasets and identify and resolve issues using Pinnacle 21 / OpenCDISC.
- Contribute to establishing a robust and reproducible programming workflow using GitHub and relevant R-based packages.
- Work collaboratively with statisticians, research strategists, and the existing statistical programmer to ensure datasets and documentation are accurate and fit for purpose.
- Support preparation of submission packages, if required.
- Perform independent double-programming and validation of datasets to ensure adherence to CDISC guidelines prior to sponsor delivery.
- Contribute to good programming practice, quality control, and documentation standards across the project.
Person Specification
Essential Experience and Skills
- Proven experience converting observational / real-world study data into CDISC SDTM and, coupled with deep, hands-on experience generating ADaM datasets and specifications from scratch.
- Strong hands-on programming experience in R, including building codebases and derivations.
- Strong experience with CDISC implementation and submission-supporting documentation.
- Experience using R-based CDISC/pharmaverse tools such as: sdtm.oak, admiral, other relevant pharmaverse packages.
- Experience writing SDTM and ADaM specifications directly from protocol and CRF/eCRF documentation.
- Experience converting annotated CRFs / EDC structures into detailed mapping specifications and transformation logic.
- Familiarity with preparing define.xml, review guides, and controlled terminology documentation.
- Experience validating datasets using Pinnacle 21 or equivalent CDISC validation tools.
- Experience using GitHub for version control, code management, and reusable workflows.
- Strong attention to detail and commitment to quality and reproducibility.
Desirable
- Previous experience supporting regulatory submission packages.
- Experience in cardiovascular, thrombosis, or other observational registry studies.
- Familiarity with biomarker, laboratory, and patient-reported outcome data.
- Working knowledge of SAS, although this is not essential for this role.
Statistical Programmer R in London employer: Pop Science
Contact Detail:
Pop Science Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Statistical Programmer R in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend relevant meetups, and engage with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your R programming skills. We recommend doing mock interviews with friends or using online platforms to get comfortable talking about your experience with CDISC datasets and statistical programming.
✨Tip Number 3
Don’t forget to follow up after interviews! A quick thank-you email can go a long way in showing your enthusiasm for the role. We suggest mentioning something specific from the interview to remind them of your conversation.
✨Tip Number 4
Apply directly through our website for the best chance at landing the job. We make it easy for you to showcase your skills and experience, so don’t miss out on the opportunity to stand out from the crowd!
We think you need these skills to ace Statistical Programmer R in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience with CDISC SDTM and ADaM datasets. We want to see how your skills in R programming and dataset specifications align with the role, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about statistical programming and how your background makes you a perfect fit for this project. We love seeing enthusiasm and a personal touch!
Showcase Your Technical Skills: Don’t forget to highlight your hands-on experience with R and any CDISC tools you've used. We’re looking for someone who can hit the ground running, so make sure we know about your coding prowess and familiarity with validation tools like Pinnacle 21.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Pop Science
✨Know Your CDISC Inside Out
Make sure you brush up on your knowledge of CDISC standards, especially SDTM and ADaM. Be ready to discuss how you've previously converted observational study data into these formats, as this will be a key focus of the role.
✨Show Off Your R Skills
Prepare to demonstrate your programming prowess in R. Bring examples of your code or projects where you've developed programming solutions and dataset specifications. This will help showcase your hands-on experience and problem-solving abilities.
✨Familiarise Yourself with Submission Documentation
Get comfortable with the types of submission-supporting documents you'll need to prepare, like the SDTM Review Guide and define.xml. Being able to talk about your experience with these documents will show that you're ready for the responsibilities of the role.
✨Collaboration is Key
Since you'll be working closely with statisticians and other team members, think of examples where you've successfully collaborated on projects. Highlight your ability to communicate effectively and contribute to a team environment, as this will be crucial for success.