Jobs at Orakl Oncology

Design and scale omics data architecture, ingestion pipelines, data models, lineage, storage layouts, and access layers. Ensure processed sequencing and molecular data is reliable, reproducible, and accessible to computational biologists and research models. Collaborate with data engineering and computational biology teams on databases, cloud storage, infrastructure, CI/CD, and model-ready datasets. Support the evolution of a large oncology data corpus and develop understanding of omics processing and bioinformatics workflows.

Build and lead Orakl’s automation function for high-throughput 3D cell-culture workflows. Responsibilities include mapping processes, defining the automation roadmap, selecting and negotiating with vendors, specifying and commissioning equipment, conducting acceptance tests, translating protocols into machine execution, monitoring performance, establishing quality and safety standards, and hiring the automation team. The role partners closely with biology, laboratory, data science, and operations teams.

Own end-to-end wet-lab data pipelines, from instrument and screening outputs to validated, analysis-ready datasets. Design the canonical data model across experimental, clinical, omics, and trial data; build quality-control systems and feedback loops; maintain production code; support lab automation and tooling; and improve operational efficiency. Work closely with scientists and technicians in an interdisciplinary oncology research environment.