Job Description We have an exciting opportunity for a Cell Painting Data Analyst to join our Research Predictive Science team within Product Safety. In this role, you will apply advanced statistical and machine learning approaches to high‑content imaging data, contributing to innovative predictive safety strategies. Working at the interface of biology, imaging, and data science, you will translate complex cell painting datasets into insights that guide early research and safety decisions. Key responsibilities will include: Processing, curating and analyzing high‑dimensional Cell Painting datasets, ensuring data quality and consistency across experiments. Developing and applying statistical and exploratory data analysis approaches to extract meaningful morphological features and phenotypic signatures. Supporting, developing and implementing computational workflows for image‑based profiling, including feature extraction, normalization, and dimensionality reduction. Collaborating with biologists and toxicologists to interpret phenotypic patterns and explore how morphological signatures may relate to cellular processes relevant to safety assessment. Evaluating and comparing analytical methods, assessing performance, robustness, and suitability for Cell Painting applications. Documenting workflows, summarizing results, and communicate findings clearly to cross‑functional scientific teams. Supporting integration of approaches into other workflows and working with RDIT teams where required to achieve robust pipelines.