Real-World Evidence Research Scientist

1w1 week ago

Novocure

Haifa, IL · Full-time · ILS 350,000 – ILS 500,000

About this role

Novocure is building a new multidisciplinary Real-World Evidence (RWE) team in oncology and clinical research. We're looking for a Real-World Evidence Research Scientist to join this exciting hybrid journey in Haifa. Together, create meaningful data-driven insights to impact healthcare.

Dive deep into complex real-world datasets including clinical data, oncology, and unexplored sources. Lead full-cycle research processes from hypothesis generation and algorithm development to data cleaning, analysis, visualization, and reporting. Perform survival analyses using advanced methods like Cox proportional hazards models and Kaplan-Meier estimators.

Write clean, high-quality code in Python and SQL with libraries like Pandas and SKLearn. Apply machine learning techniques where appropriate on large clinical datasets. Collaborate in a dynamic team culture that values knowledge sharing, peer feedback, and continuous learning.

Build something from scratch in a new knowledge domain with natural curiosity and drive. Deliver impactful insights under pressure with a business-oriented mindset. Contribute to Novocure's patient-forward mission to extend survival in aggressive cancers.

Embrace values of innovation, focus, drive, courage, trust, and empathy. Strive together with patients through innovative therapy commercialization. Join to tackle meaningful challenges in real-world evidence.

Requirements

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

Responsibilities

Dive deep into complex, real-world datasets including 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
Write clean, high-quality code (Python, SQL) and work with leading libraries (Pandas, SKLearn) and apply Machine Learning techniques where appropriate
Collaborate in a dynamic team culture that values sharing knowledge, peer feedback, and continuous learning

Benefits

Hybrid work location
Join a newly formed multidisciplinary RWE team
Dynamic culture emphasizing knowledge sharing, peer feedback, and continuous learning
Patient-forward mission to extend survival in aggressive cancers