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- Tasks: Design and execute real-world evidence studies in oncology using data analytics.
- Company: Join a leading firm focused on innovative healthcare solutions across Europe.
- Benefits: Enjoy remote work flexibility and the chance to impact patient outcomes.
- Why this job: Be part of a dynamic team driving advancements in oncology through data science.
- Qualifications: 5+ years in RWD analytics with proficiency in R or Python required.
- Other info: Immediate start available; no notice periods needed.
The predicted salary is between 54000 - 84000 £ per year.
Freelance Senior Real-World Data Science Specialist – Oncology (Remote, Europe)
ASAP START – NO NOTICE PERIODS.
Key Focus Areas:
– Design and execute RWE studies using EHR & claims data
– Hands-on work with Flatiron Health and Komodo databases
– Build scalable oncology analytics pipelines
– Collaborate cross-functionally on evidence generation
– Develop protocols, statistical plans, and support publications
What You’ll Bring:
– 5+ years in RWD analytics (EHRs, claims, registries)
– Proficient in R or Python
– Background in Biostats, Data Science or similar
– Strong grasp of observational methods and RWE standards
– Oncology experience and familiarity with causal inference, machine learning, or trial emulation
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Freelance Senior Real-World Data Science Specialist employer: Barrington James Limited
Contact Detail:
Barrington James Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Freelance Senior Real-World Data Science Specialist
✨Tip Number 1
Network with professionals in the oncology and real-world data science fields. Attend relevant webinars, conferences, or meetups to connect with potential colleagues and learn about industry trends that could give you an edge.
✨Tip Number 2
Showcase your hands-on experience with Flatiron Health and Komodo databases. If you've worked on similar projects, be ready to discuss specific challenges you faced and how you overcame them during interviews.
✨Tip Number 3
Brush up on your knowledge of observational methods and RWE standards. Being able to articulate your understanding of these concepts will demonstrate your expertise and commitment to the field.
✨Tip Number 4
Prepare to discuss your experience with statistical plans and publications. Highlight any successful projects where your contributions led to impactful results, as this will show your ability to collaborate cross-functionally.
We think you need these skills to ace Freelance Senior Real-World Data Science Specialist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in real-world data (RWD) analytics, particularly in oncology. Emphasise your proficiency in R or Python and any relevant projects you've worked on that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about oncology and how your background in biostatistics and data science makes you a perfect fit for this role. Mention specific experiences that demonstrate your ability to design and execute RWE studies.
Showcase Relevant Projects: If you have worked on projects involving Flatiron Health or Komodo databases, be sure to include these in your application. Detail your role in these projects and the outcomes achieved to illustrate your hands-on experience.
Highlight Collaboration Skills: Since the role involves cross-functional collaboration, mention any previous experiences where you successfully worked with diverse teams. This could include developing protocols or statistical plans, so be specific about your contributions.
How to prepare for a job interview at Barrington James Limited
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in R or Python during the interview. Be prepared to discuss specific projects where you've used these languages, especially in relation to real-world data analytics.
✨Demonstrate Your Oncology Knowledge
Since the role focuses on oncology, it's crucial to showcase your understanding of this field. Discuss any relevant experience you have, particularly with causal inference and machine learning applications in oncology.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world data studies. Prepare examples of how you've designed and executed RWE studies, including any challenges you faced and how you overcame them.
✨Emphasise Collaboration Skills
This role involves cross-functional collaboration, so be ready to talk about your experience working with different teams. Share examples of how you've successfully collaborated on evidence generation and supported publications.
