Senior Scientist II, Computational Biology

Role Summary

Senior Scientist II, Computational Biology. AbbVie seeks an innovative scientist to lead the integration of statistical & computational methodologies into analysis workflows for Complex In Vitro Models (CIVM), including organoids, organ-on-a-chip, and advanced multicellular systems. The role will champion multi-modal phenotyping, manage centralized metadata, and develop robust pipelines for hypothesis testing, causal inference, and predictive modeling using multi-omics datasets. The ideal candidate will standardize and harmonize data formats and workflows across Immunology sites, collaborating with researchers to build scalable, reproducible data pipelines.

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.

Qualifications

• Required: BS, MS, or PhD in Biophysics, Biology, Mathematics, Engineering, Pharmacology or related discipline with typically 12+ (BS), 10+ (MS), or 4+ (PhD) years of experience and a strong track record in computational biology and life science research.
• Required: Minimum 3 years of hands-on experience in computational analysis, algorithm development, and statistics.
• Required: Solid biological domain knowledge and ability to bridge computational and experimental perspectives.
• Required: Exceptional written and verbal communication skills with demonstrated ability to communicate modeling approaches, assumptions, results, and limitations to technical and non-technical stakeholders.
• Preferred: Experience with imaging technologies, functional assays, and data analysis for complex in vitro models.
• Preferred: Proven record of developing or deploying statistical or AI/ML tools in research, especially in the context of 3D tissue models, organoids or related platforms in a drug discovery or translational research setting.