AbbVie is seeking an innovative and technically proficient scientist to lead the integration of statistical and computational methodologies into analysis workflows for Complex In Vitro Models (CIVM), including organoids, organ-on-a-chip, and advanced multicellular systems. This role will champion multi-modal phenotyping, manage centralized metadata, and drive the development of robust pipelines for hypothesis testing, causal inference, and predictive modeling using multi-omics datasets. The ideal candidate will be instrumental in standardizing and harmonizing data formats and workflows across Immunology sites, collaborating with researchers to build scalable, reproducible data pipelines.

Key Responsibilities:

• Integrate statistical analysis and computational techniques into multimodal data workflows (imaging, spatial omics, etc.) to extract actionable biological insights.
• Collaborate with discovery scientists to design and analyze experiments, translating human-derived hypotheses into mechanistic wet lab assays.
• Lead development of scalable, reproducible pipelines for hypothesis testing, causal inference, and predictive modeling across imaging and multi-omics datasets.
• Guide statistical planning for in vitro (and in vivo studies as needed), including power/sample size calculations, randomization, and reproducibility standards.
• Ensure statistical rigor and appropriate evaluation strategies in interpreting experimental results, supporting go/no-go decisions and milestone reviews, especially for data from in vitro assays.
• Work closely with translational scientists, imaging scientists, bioinformaticians, and pathologists to translate scientific questions into computational solutions.
• Balance innovation with practicality, ensuring solutions are scalable, interpretable, and fit-for-purpose.
• Mentor junior scientists and foster a collaborative, innovative research environment.