Staff Data Scientist, Machine Learning
Valo HealthFull Time
Junior (1 to 2 years), Senior (5 to 8 years)
The ideal candidate should possess a PhD (or equivalent experience) in machine learning, computational biology, bioinformatics, computer science, or a related field, along with at least 3 years of relevant experience. Demonstrated expertise in applying deep learning to omics data at scale is required, as well as proficiency in Python and modern deep-learning frameworks such as PyTorch or JAX. A solid grasp of causal inference, experimental design, and statistics is also necessary, along with familiarity with software engineering best practices, version control, and continuous integration.
This Machine Learning Scientist II/Sr (Omics) 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 code and deploy models, stay current with advancements in machine learning and computational biology, and mentor colleagues in best practices.
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.