Staff Data Scientist, Machine Learning
Valo HealthFull Time
Junior (1 to 2 years), Senior (5 to 8 years)
Candidates should possess a PhD (or equivalent experience) in Machine Learning, Computational Biology, Bioinformatics, Computer Science, or a related field, with a minimum of 3 years of relevant experience. Demonstrated expertise in applying deep learning techniques to omics data at scale is required, along with proficiency in Python and modern deep-learning frameworks such as PyTorch or JAX. A solid understanding of causal inference, experimental design, and statistics is essential, as is familiarity with software engineering best practices, including version control and code review.
The Machine Learning Scientist will identify, prioritize, and acquire multi-omics datasets, build and maintain data pipelines for ingesting and harmonizing large datasets, design schemes for pretraining and finetuning models, define benchmarks for target-selection and biomarker tasks, apply causal inference principles to propose experiments, write high-quality tested code and deploy models, and stay current with advances in machine learning and computational biology while mentoring colleagues in data engineering, modeling, and experimental design.
Develops therapies for CNS disorders
Axsome Therapeutics develops therapies for central nervous system (CNS) disorders, focusing on conditions like major depressive disorder, treatment-resistant depression, and Alzheimer's agitation. Their main product, AXS-05, is an oral medication that works by blocking NMDA receptors in the brain, which helps regulate mood. This drug has shown positive results in clinical trials and has received special FDA status to speed up its approval process. Unlike many competitors, Axsome emphasizes addressing unmet medical needs in CNS disorders and aims to improve patient outcomes through rigorous research and development. The company's goal is to bring effective treatments to market, enhancing the quality of life for patients suffering from these conditions.