Data Scientist - Innovation - PhD

Role: Data Scientist in Caris's Innovation Team focused on developing AI models for cancer diagnostics using molecular sequencing data. Responsibilities include processing large NGS datasets (WGS, WES, RNA-seq, cfDNA), creating algorithms for biomarker discovery, applying state-of-the-art machine learning/deep learning techniques, and translating research questions into analytical problems. The role involves leading projects from problem framing to deployment, contributing to scientific publications, and shaping analytical methods for clinical impact. Qualifications: PhD in Data Science, Bioinformatics, Computational Biology, or related fields; up to 2 years postdoctoral experience; hands-on expertise with sequencing data and ML/DL (PyTorch, transformers); peer-reviewed publications; strong Python and Linux skills. Preferred skills include multi-omics integration, epigenetics, cloud platforms (AWS), containerization (Docker), and interest in liquid biopsy and early cancer diagnostics. The position is based in Irving, TX, requiring onsite work with close collaboration, and may involve relocation. The role emphasizes innovation in translational oncology, leveraging proprietary clinical datasets, and working at the intersection of research and clinical decision-making.