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- Tasks: Develop and validate R packages for clinical trial analysis and train team members.
- Company: Join a leading pharmaceutical company dedicated to advancing healthcare through innovative data solutions.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team making a real impact in clinical research and data science.
- Qualifications: 5+ years of R programming experience in clinical trials; strong skills in data visualization and statistical methodology.
- Other info: Exposure to Late Phase & Real-World Evidence studies is a plus.
The predicted salary is between 48000 - 72000 £ per year.
Responsibilities
- Develop internal and external R packages for clinical trial analysis (ADaM, tables, figures, listings).
- Validate R packages.
- Lead implementation in R and train other Biostatistics team members.
- Create and validate all safety and efficacy study output requirements (e.g., ADaM, TLFs) in accordance with data definitions, specifications, and relevant study documentation (e.g., protocol, SAP, aCRF).
- Conduct statistical programming work of clinical data using R.
- Identify problems and develop global tools to increase the efficiency and capacity of the Statistical Programming group.
- Collaborate with peers and statisticians to ensure the quality and accuracy of clinical data, ensuring submission readiness (e.g., SDTM, ADaM, tables, figures, listings, define.xml).
Experience and Qualifications
- Minimum 5+ years of experience in R programming for clinical trial data, including developing and validating R packages from CRO or Pharmaceutical Industry.
- Strong programming skills in R and R Shiny.
- Strong understanding of end-to-end Clinical Trials in Statistical Programming is mandatory.
- Exposure to Late Phase & Real-World Evidence (RWE) studies is highly desirable.
- Proven experience in applying R and R-Shiny for the analysis and reporting of clinical trials, with the ability to reproduce statistical analysis using R.
- Strong skills in data visualization and data wrangling using R, including proficiency with R packages for data exploration and visualization.
- Application of statistical methodology and concepts in clinical trial analysis, including experience with R-Shiny apps for data exploration.
- Advanced knowledge of industry standards including CDISC data structures and a solid understanding of the development and use of standard programs.
- In-depth understanding of the phases of clinical trials and the drug development process.
Contact Detail:
IQVIA, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Clinical Data Scientist
✨Tip Number 1
Make sure to showcase your experience with R programming and R Shiny in your conversations. Highlight specific projects where you've developed or validated R packages, as this will resonate well with the hiring team.
✨Tip Number 2
Network with professionals in the clinical data science field, especially those who have worked on late-phase and real-world evidence studies. Engaging with them can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your understanding of CDISC data structures and how they apply to clinical trials. Being able to articulate this knowledge during interviews will demonstrate your expertise and readiness for the role.
✨Tip Number 4
Familiarise yourself with the latest trends and tools in statistical programming for clinical trials. Showing that you are up-to-date with industry standards and innovations can set you apart from other candidates.
We think you need these skills to ace Senior Clinical Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with R programming, particularly in clinical trial data analysis. Emphasise any specific projects where you developed or validated R packages, as well as your familiarity with ADaM and TLFs.
Craft a Strong Cover Letter: In your cover letter, explain why you're passionate about the role of Senior Clinical Data Scientist. Mention your experience with late-phase studies and R-Shiny apps, and how these skills can contribute to the company's goals.
Showcase Relevant Projects: Include examples of past projects that demonstrate your ability to conduct statistical programming work using R. Highlight any tools you've developed to improve efficiency within a team, as this aligns with the job's responsibilities.
Highlight Collaboration Skills: Since collaboration is key in this role, mention any experiences where you've worked closely with statisticians or peers to ensure data quality and accuracy. This will show that you can thrive in a team environment.
How to prepare for a job interview at IQVIA, Inc.
✨Showcase Your R Expertise
Be prepared to discuss your experience with R programming in detail. Highlight specific projects where you've developed and validated R packages, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Statistical Knowledge
Make sure to brush up on statistical methodologies relevant to clinical trials. Be ready to discuss how you've applied these concepts in your previous roles, especially in relation to ADaM and TLFs.
✨Prepare for Technical Questions
Expect technical questions related to R and R-Shiny. Practice coding problems or scenarios that may come up during the interview, as this will demonstrate your problem-solving skills and technical proficiency.
✨Emphasise Collaboration Skills
Since collaboration is key in this role, be prepared to share examples of how you've worked with peers and statisticians in the past. Discuss how you ensured data quality and accuracy in your projects.
