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For Companies At a Glance
- Tasks: Analyse real world data and provide expert statistical support for clinical studies.
- Company: Join a leading firm in Real World Evidence with a flexible, remote work culture.
- Benefits: Enjoy a zero-hours contract with competitive pay and the freedom to work from anywhere.
- Why this job: Make a real impact in healthcare by delivering high-quality analyses and collaborating with experts.
- Qualifications: MSc in Statistics or related field with 10-15 years of relevant experience.
- Other info: Perfect for independent thinkers who thrive in a dynamic, project-based environment.
The predicted salary is between 22 - 30 £ per hour.
Contract Real World Evidence Statistician – RWE Analysis (Zero Hours Contractor)
Location: Remote / Flexible
Contract Type: Zero Hours Specialist Contractor (Time and Materials)
Function: Statistics / Real World Evidence
About the Role
We are seeking an experienced RWE, Real World Evidence Statistician to provide specialist statistical support for RWE clinical studies on a flexible, zero-hours contract basis. This role focuses on delivering high-quality RWE analyses, quality control activities, and analytical peer review in line with study protocols, Statistical Analysis Plans (SAPs), and regulatory expectations. This is an ideal opportunity for a contractor who enjoys working independently within a defined analytical scope while collaborating with multidisciplinary clinical development teams.
Key Responsibilities
- Real World Evidence Data Analysis and Reporting
- Perform standard real world analysis studies
- Provide expert statistical input into the design of observational and non-interventional studies using real world data (RWD)
- Advise on appropriate study designs (e.g. pre/post, cohort, matched comparator, benchmark-aligned analyses) and their limitations
- Define analytically sound frameworks for outcomes reporting aligned to the intended use (e.g. external credibility rather than regulatory submission)
- Quality Control and Review
- Act as an independent statistical expert reviewing client-generated RWE analyses
- Provide written and verbal critique of analytical approaches and outputs
- Support refinement of outcomes reporting to improve credibility and external acceptance
- Peer review analyses performed by other statisticians or programmers
- Document QC findings clearly and support issue resolution in line with SOPs and good statistical practice
- Client-Facing Scientific Support
- Engage directly with sponsors to understand clinical services, data sources, and stakeholder objectives
- Participate in scientific discussions with clinicians, medical leadership, and external partners
- Represent Quanticate as an independent, authoritative biometrics partner in RWE discussions
- Training and Thought Leadership
- Provide internal guidance or training on RWE methodology and good practice
- Contribute to white papers, methodological guidance, or thought leadership content in RWE
- Support development of repeatable RWE analysis frameworks for ongoing client use
Contract Details
- Flexible zero-hours arrangement based on project demand
- Time and materials engagement model
- Opportunity to support a range of early-phase clinical development programmes
- Fully remote working environment
How to Apply
Please submit your CV outlining relevant PK analysis experience and availability for contract work.
About You
Qualifications and Knowledge
- Expert understanding of observational study design and analysis
- Deep knowledge of RWE/RWD principles, strengths, and limitations
- Strong grounding in causal inference concepts, bias, and confounding
- Working knowledge of relevant guidance (e.g. FDA RWE Framework, EMA guidance, ISPOR good practice)
- Minimum qualification: MSc in Statistics or related quantitative discipline (or equivalent experience)
Experience
- Typically 10-15 years’ experience in pharmaceutical, healthcare, CRO, or academic settings
- Demonstrated experience delivering independent RWE or outcomes research consultancy
- Proven ability to review, challenge, and refine non-interventional analyses
- Experience working with medical record–derived or routinely collected healthcare data
Technical Skills
- Proficiency in SAS and/or R; familiarity with real world data structures
- Ability to explain complex methodological issues clearly and proportionately
- Strong analytical accuracy and attention to detail
- Ability to work independently while adhering to defined specifications
Zero Hour Contract - Statistician - Real World Evidence United Kingdom Statistics employer: QUANTICATE INTERNATIONAL LIMITED
Contact Detail:
QUANTICATE INTERNATIONAL LIMITED Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Zero Hour Contract - Statistician - Real World Evidence United Kingdom Statistics
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend virtual meetups, and engage in discussions on platforms like LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that perfect gig.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your RWE analyses and projects. This is your chance to demonstrate your expertise in observational study design and statistical methods. We recommend sharing this on your personal website or LinkedIn profile to catch the eye of potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to RWE and statistical analysis. We suggest practising your responses with a friend or even in front of a mirror. Confidence is key, and being well-prepared will help you shine during those crucial conversations.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got a range of opportunities that might be just what you’re looking for. Plus, applying directly can sometimes give you an edge over other candidates. So, get your CV ready and let’s make it happen!
We think you need these skills to ace Zero Hour Contract - Statistician - Real World Evidence United Kingdom Statistics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in RWE and statistics. We want to see how your skills match the job description, so don’t be shy about showcasing your expertise!
Showcase Your Independence: Since this is a zero-hours contract, it’s important to demonstrate your ability to work independently. Share examples of past projects where you’ve taken the lead and delivered results without constant supervision.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about your qualifications and experiences that relate to the role.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at QUANTICATE INTERNATIONAL LIMITED
✨Know Your RWE Inside Out
Make sure you brush up on your knowledge of Real World Evidence (RWE) and Real World Data (RWD). Be prepared to discuss specific methodologies, study designs, and their limitations. This will show that you’re not just familiar with the concepts but can also apply them in practical scenarios.
✨Prepare for Technical Questions
Expect questions about statistical analysis tools like SAS and R. Have examples ready that demonstrate your proficiency and how you've used these tools in past projects. Being able to explain complex statistical concepts clearly will set you apart from other candidates.
✨Showcase Your Independent Working Style
Since this role involves working independently, be ready to share examples of how you've successfully managed projects on your own. Highlight your ability to adhere to specifications while delivering high-quality analyses, as this is crucial for a zero-hours contract position.
✨Engage in Scientific Discussions
Demonstrate your ability to engage with clinical teams and stakeholders. Prepare to discuss how you would approach scientific discussions and provide insights into how you can contribute to multidisciplinary teams. This shows that you’re not just a statistician but a collaborative partner in the research process.