Real-World Evidence Scientis

Novocure is a global, publicly-traded commercial-stage oncology company developing a profoundly different cancer treatment therapy called tumor-treating fields (TTFields) for patients with solid tumors. TTFields therapy is a non-invasive, novel, antimitotic treatment modality that utilizes proprietary technology, attempting to slow or reverse tumor progression by inducing tumor cell death.

Novocure's commercialized product, Optune, is approved for the treatment of adult patients with glioblastoma (GBM) in the USA, Europe, and Israel.

Novocure has ongoing or completed clinical trials and is further expanding its efforts into several other solid tumor indications - non-small cell lung cancer, pancreatic cancer, and other types of solid cancers.

We are looking for a Real-World Evidence Scientist who will join our Real-World Evidence group in Israel.

In this role, you will work in a multi-disciplinary environment involving data, biology and clinical experts.

This full-time position is to report to the Head of Real-World Evidence and is located at our R&D center, Haifa, Israel

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Utilize proven methodologies and advanced technical skills to work with a wide range of data types, scales, and big data, exploring and generating data-driven insights in the context of clinical research in oncology.
• Perform survival analysis using advanced methods and analyze temporal processes.
• Lead research projects end-to-end, guide collaborators and report findings to stakeholders.
• Work closely with a multidisciplinary team of experts to translate statistical findings into clinical insights and actionable treatment strategies.
• Collaborate with medical professionals to enrich medical datasets, using internal and external data resources.
• Take an active role in the full cycle of iterative data exploration, including hypothesis development, algorithm design, data cleaning, testing, insight extraction, and data visualization.
• Ability to identify when Machine Learning techniques are appropriate and apply them effectively for data analysis.
• Write or contribute to writing reports and publications describing research findings.
• Stay updated with the latest research and best practices in the field of Real-World Evidence and therapeutic areas under investigation.

QUALIFICATIONS/KNOWLEDGE:

Qualifications:

• MSc or PhD in a computational or statistical field (e.g., Computer Science/ Statistics/ Applied Mathematics/ Software Engineering/ Operations Research/ Biomedical Engineering) or equivalent experience.

Knowledge:

• At least 4 years of experience in Data Science or research positions involving clinical data.
• Strong background in Machine Learning techniques.
• Skilled and experienced in Python and SQL programming.
• Outstanding intuition for working with data.
• Proficient with data analytics tools and frameworks, including platforms such as SKLearn, NumPy, Pandas, and SparkSQL.
• Experience modeling clinical data using Cox proportional hazards models, Kaplan-Meier estimators, and competing risks models.
• Ability to contribute to study designs, incorporating methods such as adaptive design, superiority, non-inferiority, propensity score matching, and meta-analysis.
• Experience working with temporal (time-dependent) data models.
• Independent problem solver, capable of addressing complex algorithmic challenges with minimal supervision.
• Capable of providing statistical consulting and overseeing statistical components of clinical research projects.
• Proven ability to lead research projects from inception to completion and collaborate effectively with fellow statisticians and data scientists.
• Experience with oncology research - an advantage.
• Knowledge of LLM (Large Language Model) technologies - an advantage.
• Familiarity with bioinformatics - an advantage.
• Experience with cloud platforms such as AWS or Google Cloud Platform - an advantage.
• Team-oriented, with the ability to collaborate within multidisciplinary teams including software engineers, physicists, algorithm developers, and medical professionals
• Fluent in English (spoken and written) with excellent communication skills.

OTHERS:

• Fast learner, flexible, and capable of thriving in a high-paced environment.
• Strong verbal and written communication skills, including the ability to lead meetings, deliver professional presentations, and explain complex technical concepts to non-technical stakeholders.