• Apply and adapt machine learning and statistical modeling approaches for biomarker discovery and longitudinal disease tracking. • Build scalable, production-ready analysis pipelines that meet clinical-grade performance standards. • Drive the adoption and refinement of machine learning best practices, including model interpretability, uncertainty estimation, and reproducibility. • Design computational strategies for ultrasensitive variant calling, error suppression, and signal extraction from sequencing data. • Collaborate cross-functionally with bioinformatics and data scientists, R&D and clinical teams to explore new ML approaches and evaluate their potential impact. • Actively participate in code and design reviews, with a focus on ML model quality, reproducibility, and integration into production pipelines.