Teams at Eli Lilly and Company

Owns the scientific integrity of automated discovery oncology workflows. Responsibilities include designing and validating assays, defining QC and controls, reviewing automated workflows, investigating scientific root causes, setting data quality standards, evaluating assay technologies, and partnering with engineers and informatics teams. The role also contributes to scientist-facing dashboards, interfaces, and automation tools, mentors colleagues, and supports trustworthy downstream data interpretation.

Leads architecture, software, controls, and usability for automated laboratory systems supporting oncology discovery. Designs workcells, liquid-handling integrations, user interfaces, data pipelines, monitoring tools, and diagnostic systems. Partners with scientists, software and hardware engineers, vendors, and platform leaders; oversees installation, validation, optimization, and root-cause resolution. Provides technical direction and mentorship while remaining hands-on with automation software, APIs, configuration, and AI-assisted tooling.

Lead development and scaling of spatial transcriptomics and long-read sequencing platforms for Oncology discovery. Design tissue and library workflows, optimize sample processing, automate NGS protocols, develop image and computational pipelines, integrate multimodal spatial and single-cell data, set QC benchmarks, advise project teams, and mentor junior scientists while managing vendor and collaborator relationships.