Sr. Data Scientist- Drug Discovery

Who We Are:

At Neurocrine Biosciences, we pride ourselves on having a strong, inclusive, and positive culture based on our shared purpose and values. We know what it takes to be great, and we are as passionate about our people as we are about our purpose - to relieve suffering for people with great needs.

What We Do:

Neurocrine Biosciences is a leading neuroscience-focused, biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs. We are dedicated to discovering and developing life-changing treatments for patients with under-addressed neurological, neuroendocrine and neuropsychiatric disorders. The company's diverse portfolio includes FDA-approved treatments for tardive dyskinesia, chorea associated with Huntington's disease, classic congenital adrenal hyperplasia, endometriosis* and uterine fibroids,* as well as a robust pipeline including multiple compounds in mid- to late-phase clinical development across our core therapeutic areas. For three decades, we have applied our unique insight into neuroscience and the interconnections between brain and body systems to treat complex conditions. We relentlessly pursue medicines to ease the burden of debilitating diseases and disorders because you deserve brave science. For more information, visit neurocrine.com, and follow the company on LinkedIn, X and Facebook. (*in collaboration with AbbVie)

About the Role:

Plays a strong role in advancing neuroscience drug development programs using innovative data science and informatics approaches and pipelines. The initial focus will be in advancing AI/Machine learning (ML) capabilities by using diverse multi-omics datasets to understand mechanisms of drug action and enhance our drug programs through AI/ML predictive tools. Supports preclinical and clinical studies, coordinates complex sequencing datasets, and guides collaborative projects to ensure effective communication and coordination.

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Your Contributions:

• Research, expand, and validate analytical models using leading AI/ML techniques, including supervised and unsupervised learning, deep learning, and transformer models

• Supports development of reliable and impactful AI/ML model approaches into production environments

• Train and fine-tune AI models using internal datasets

• Continuously refine processes and workflows to boost efficiency, effectiveness, and reproducibility of AI/ML solutions

• Analyze large, complex sequencing datasets, including single brain cells and cell lines

• Integrate multi-omics (RNA-seq, proteomics), imaging, and clinical trial datasets into AI pipelines

• Leverage scRNASeq to contextualize target gene expression in the context of cell types, disease biology and phenotypes

• Build and implement AI/ML techniques to build pipelines for antibody design and optimization including structure prediction, sequence modeling and representation, affinity, selectivity, and drug-like properties

• Drives cross-team projects and external initiatives to integrate AI/ML models into drug discovery pipelines, ensuring effective communication and coordination

• Stay current with industry trends and apply best practices to improve internal tools and processes

• Develop methods for integrating and visualizing multi-omics data

• Implement quality control measures and standard operating procedures

• Prepare detailed reports,