At a Glance
- Tasks: Generate Data Management listings from clinical trial data using SAS and support key milestones.
- Company: Join Veramed, a leader in clinical data management with a global reach.
- Benefits: Gain valuable experience in clinical trials and potential for career advancement.
- Other info: Opportunity to learn SDTM programming and work in a supportive environment.
- Why this job: Be part of a dedicated team making a real difference in healthcare through data.
- Qualifications: Experience with SAS programming and a passion for data management.
The predicted salary is between 54000 - 66000 £ per year.
Veramed is seeking a Data Management Programmer to join a sponsor-dedicated team, working as a fully integrated member of a global Data Management Programming function. The role focuses on generating Data Management listings from raw clinical trial data using SAS, with an opportunity to gain exposure to SDTM programming over time.
You will generate listings, draft Define.xml and SDRG documentation, and support milestones such as Dry Runs and Interim Analyses while ensuring adherence to sponsor.
SDTM/Data Management SAS Programmer | Clinical Trials employer: Veramed
Veramed is an exceptional employer that prioritises employee growth and development within a warm and friendly working environment. With flexible working options, including remote and hybrid roles, and a strong focus on training and support, employees are empowered to advance their careers while contributing to innovative studies in the clinical research field. The company's unique approach to management fosters collaboration and encourages staff to take ownership of their roles, making it an ideal place for Statistical Programmers looking for meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land SDTM/Data Management SAS Programmer | Clinical Trials
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We think you need these skills to ace SDTM/Data Management SAS Programmer | Clinical Trials
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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Craft a Tailored Cover Letter:For a full-time role at Veramed, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Veramed. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Veramed
✨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 a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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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.
