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- Tasks: Join us as a Statistical Programmer and analyze clinical data for impactful projects.
- Company: Planet Pharma is a leading global organization in the pharmaceutical industry.
- Benefits: Enjoy a full-time permanent position with opportunities for professional growth.
- Why this job: Make a difference in healthcare while working with cutting-edge data science techniques.
- Qualifications: Bachelor’s or Master’s in Statistics, Mathematics, or related field required.
- Other info: Must reside in the UK; oncology experience is a plus.
The predicted salary is between 36000 - 60000 £ per year.
Planet Pharma is pleased to be recruiting for a Statistical Programmer to work on a full-time permanent basis for a leading, global organisation in the UK.
***Please note you must reside in the UK***
Ideally we are seeking someone with proven experience of working as a Statistical Programmer within the pharmaceutical industry.
You should also hold the following;
- Bachelor’s or Master’s in Statistics, Mathematics, or related field or equivalent.
- Substantial experience in clinical data standards ADAMS, TLFs, and submission guidelines.
- Hands-on programming experience within one or more statistical/data science programming languages (e.g., R, SAS, or Python). This includes writing code to manipulate data and analyse a wide array of data sources/types.
- Knowledge of the data science lifecycle and process flow (e.g., ETL, data quality, statistical data analysis, machine learning, data randomization.
- Knowledge of study documents such as Protocol, SAP, TLF specs, and data specification.
- Oncology experience is desirable.
Planet Pharma | Statistical Programmer employer: Planet Pharma
Contact Detail:
Planet Pharma Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Planet Pharma | Statistical Programmer
✨Tip Number 1
Make sure to highlight your hands-on programming experience in R, SAS, or Python during any networking opportunities. Engage with professionals in the pharmaceutical industry on platforms like LinkedIn to showcase your skills and connect with potential colleagues.
✨Tip Number 2
Familiarize yourself with the latest clinical data standards and submission guidelines. Consider joining relevant online forums or groups where you can discuss these topics and stay updated on industry trends.
✨Tip Number 3
If you have oncology experience, be sure to mention it in conversations with industry professionals. This niche expertise can set you apart from other candidates and may lead to valuable referrals.
✨Tip Number 4
Attend industry conferences or webinars focused on statistical programming and data science in the pharmaceutical sector. These events are great for networking and can help you learn more about what companies like Planet Pharma are looking for in candidates.
We think you need these skills to ace Planet Pharma | Statistical Programmer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Statistical Programmer, especially within the pharmaceutical industry. Include specific programming languages you are proficient in, such as R, SAS, or Python, and any relevant projects you've worked on.
Craft a Strong Cover Letter: In your cover letter, emphasize your educational background in Statistics or Mathematics and your hands-on programming experience. Mention your familiarity with clinical data standards and any oncology experience you may have.
Showcase Relevant Skills: Clearly outline your knowledge of the data science lifecycle, including ETL processes, data quality, and statistical data analysis. This will demonstrate your comprehensive understanding of the role.
Proofread Your Application: Before submitting, carefully proofread your application materials for any errors or inconsistencies. A polished application reflects your attention to detail, which is crucial in statistical programming.
How to prepare for a job interview at Planet Pharma
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on programming experience in languages like R, SAS, or Python. Bring examples of how you've manipulated and analyzed data in previous roles, as this will demonstrate your technical proficiency.
✨Understand Clinical Data Standards
Familiarize yourself with clinical data standards such as ADaM and TLFs. Be ready to explain how you have applied these standards in your work, as this knowledge is crucial for the role.
✨Discuss the Data Science Lifecycle
Make sure you can articulate your understanding of the data science lifecycle, including ETL processes and statistical data analysis. This will show that you grasp the broader context of your work and its impact on clinical studies.
✨Prepare for Oncology-Specific Questions
If you have oncology experience, be ready to discuss it in detail. If not, research common oncology study protocols and be prepared to talk about how your skills can transfer to this area.
