Real-World Evidence Research Scientist

We’re Hiring: Real-World Evidence Research Scientist

Location: Hybrid | Field: Oncology & Clinical Research

We’re building a new multidisciplinary Real-World Evidence (RWE) team — and we’re looking for a Real-World Evidence Research Scientist to join us on this exciting journey!

This is a unique opportunity to be part of a newly formed team, where each member brings a different expertise, and together we’ll create meaningful data-driven insights to impact the world of healthcare.

What will you do?

• Dive deep into complex, real-world datasets — clinical data, oncology, and other unexplored data sources.
• Lead full-cycle research processes: hypothesis generation, algorithm development, data cleaning, analysis, visualization and reporting of research findings.
• Perform survival and other statistical analyses using advanced methods on large clinical datasets including Cox proportional hazards models, Kaplan-Meier estimators, temporal data models, propensity score matching etc.
• Write clean, high-quality code (Python, SQL) and work with leading libraries (such as: Pandas, SKLearn) and apply Machine Learning techniques where appropriate.
• Collaborate in a dynamic team culture that values sharing knowledge, peer feedback, and continuous learning.

What are we looking for?

• MSc or PhD in a quantitative field (Computer Science, Statistics, Applied Mathematics, Biomedical Engineering).
• 4+ years of experience as a Data Scientist or Researcher working with clinical data.
• Proven ability to work with large-scale datasets, integrate multiple data sources, and build efficient processes.
• A natural curiosity, eagerness to learn, and drive to lead a new knowledge domain within the team.
• Ability to perform under pressure, deliver impactful insights, and think with a business-oriented mindset.

If you’re looking for a chance to build something from scratch, love working with data, and want to tackle meaningful challenges — we’d like to hear from you!