At a Glance
- Tasks: Conduct analyses for epidemiologic studies using real-world data and programming skills.
- Company: Join Planet Pharma, a top staffing firm recognised for excellence.
- Benefits: Remote work, competitive salary, and opportunities for career growth.
- Other info: Dynamic team with a commitment to diversity and inclusion.
- Why this job: Make a real impact in healthcare by analysing vital data.
- Qualifications: 5+ years in RWE data manipulation and strong R or SAS skills.
The predicted salary is between 36000 - 60000 € per year.
Statistical Analyst in Nottingham employer: LinkedIn
At Planet Pharma, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. Our remote working model allows for flexibility while providing extensive opportunities for professional growth in the field of Real World Evidence analysis. With a commitment to excellence recognised by industry awards, we ensure our employees are supported in their career development within a diverse and inclusive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Statistical Analyst in Nottingham
✨Tip Number 1
Networking is key! Reach out to professionals in the field of epidemiology and biostatistics. Join relevant online forums or LinkedIn groups where you can connect with others and learn about job openings that might not be advertised.
✨Tip Number 2
Prepare for interviews by brushing up on your R and SAS programming skills. Be ready to discuss specific projects you've worked on, especially those involving real-world evidence data. Show them you know your stuff!
✨Tip Number 3
Don’t underestimate the power of a strong personal brand. Update your LinkedIn profile to reflect your skills and experiences related to statistical analysis and real-world evidence. Make it easy for recruiters to see why you’re the perfect fit!
✨Tip Number 4
Apply directly through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to apply directly. Let’s get you that Statistical Analyst role!
We think you need these skills to ace Statistical Analyst in Nottingham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Statistical Analyst role. Highlight your experience with RWE data and programming skills in R or SAS. We want to see how your background fits perfectly with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about epidemiology and how your skills can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Relevant Experience:When filling out your application, be sure to showcase any relevant projects or roles you've had that involved cohort selection or data management. We’re keen on seeing how you’ve tackled similar challenges in the past.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application directly. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at LinkedIn
✨Know Your Data
Make sure you brush up on your experience with real-world evidence data. Be ready to discuss specific projects where you've manipulated large datasets, like claims or EMR data. This will show that you understand the complexities involved and can hit the ground running.
✨Master Your Programming Skills
Since strong R or SAS programming skills are crucial for this role, be prepared to talk about your proficiency in these languages. Consider bringing examples of code you've written or analyses you've conducted to demonstrate your expertise.
✨Understand Good Programming Practices
Familiarise yourself with RWE Good Programming Practices and QA/QC standards. During the interview, mention how you’ve implemented these practices in past projects, as it shows your commitment to quality and compliance.
✨Prepare for Scenario Questions
Expect scenario-based questions that assess your problem-solving skills in epidemiologic studies. Think of situations where you had to make decisions based on data analysis and be ready to explain your thought process clearly.