Senior Scientist, Machine Learning, Molecular Discovery

$109,000 - $150,700/Yr

Web-atrio - San Diego, CA

Full-time - Senior

San Diego, CA

About the position

The Senior Scientist in Machine Learning for Molecular Discovery at Bristol Myers Squibb will be a key member of the Predictive Sciences team, focusing on the application of advanced AI/ML techniques to develop novel small-molecule therapies. This role involves collaborating with a multidisciplinary team to enhance the design and evaluation of therapeutic compounds, driving innovative research in targeted protein degradation.

Responsibilities

• Build and apply advanced deep learning models to predict molecular attributes that govern protein degradation, cellular phenotype, and disease state.
• Leverage AI/ML approaches to guide experimental study design and steer chemical design efforts towards small molecules with high therapeutic value.
• Analyze chemistry, proteomics, transcriptomics, and other high-throughput assay data from internal, public, and partner sources.
• Collaborate as a member of cross-functional teams to validate in silico findings and improve ML workflows.
• Author scientific reports, and present methods, results, and conclusions to publishable standard.
• Contribute to planning and execution of collaborative projects with leading academic and commercial research groups worldwide.

Requirements

• Bachelor's Degree with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field and 7+ years of academic/industry experience.
• OR Master's Degree with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field and 5+ years of academic/industry experience.
• OR PhD with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field and 2+ years of academic/industry experience.

Nice-to-haves

• Ph.D. with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field.
• 2+ years postdoctoral experience applying computational research approaches in pharma/biotech, university, or hospital environments.
• Strong experience in applying contemporary deep learning methods, preferably with demonstrated application of either active, generative, graph-based, or geometric deep learning approaches.
• Expertise in scientific programming languages (e.g., Python, R) and libraries (e.g., PyTorch, Tensorflow), cloud-based computing, and data manipulation.
• Demonstrated problem-solving skills, adaptability across disciplines, and collaborative nature.
• Excellent verbal and written communication skills.

Benefits

• Competitive salary range from $109,000-$150,700 plus incentive cash and stock opportunities.
• Wide variety of competitive benefits, services, and programs to support employee goals.