Clinical Data Researcher

About Imagene

Imagene is a pioneering company in AI-based precision oncology, dedicated to decoding cancer using biopsy images. Our mission is to unlock the power of Oncology Intelligence to transform cancer research and diagnostics.

Imagene’s OI Suite platform leverages our state-of-the-art vision foundation model to provide fast, user-friendly, and data-efficient AI to advance drugs into the clinic. LungOI, our first application, is an AI-based NSCLC multi-gene test that offers rapid biomarker profiling, facilitating informed clinical decisions.

Imagene has been awarded the Digital Health Award for “Best Use of AI in HealthTech” and the Technology Leadership Best Practices Award by Frost & Sullivan and is committed to advancing precision oncology and enhancing care for cancer patients worldwide.

About the Position

We’re looking for a Clinical Data Researcher to join a cross-functional data team dedicated to powering AI-driven oncology solutions. In this role, you will lead the definition, extraction, curation, and validation of complex, diverse clinical datasets. You’ll ensure the precision, consistency, and usability of oncology data, significantly enhancing the ability of our data science team to derive high-impact, actionable insights.

Responsibilities

• Identify and curate large-scale oncology clinical datasets to support the development of AI models.
• Build reproducible, scalable pipelines for extracting, cleaning, validating, and managing clinical data.
• Use various technological tools to develop and automate data processing workflows.
• Work in an interdisciplinary team of clinicians, data engineers, and AI researchers to bridge the gap between clinical knowledge and technical implementation.

Requirements

• MD or PhD in epidemiology, public health, or another clinically focused field.
• Understanding of oncology clinical research and specifically clinical trials.
• Ability to adapt quickly to evolving tools and project requirements in a fast-paced research environment.
• Strong analytical skills, problem-solving ability, and attention to detail.
• Experience analyzing clinical datasets, including clinical trial data - advantage.
• Experience automating large-scale data processing using various tools - advantage.
• Experience working with programming languages (such as Python, primarily for automation) - advantage.