Senior Scientist, Machine Learning and Bioinformatics

Key Skills

Aartificial intelligence, Analytical and Problem solving, Bioinformatics, Effective communication skills, Machine learning techniques, Python Programming, PyTorch, R Programming, TensorFlow

Job Description

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

When you join BMS, you are joining a diverse, high-achieving team united by a common mission. 

The Informatics and Predictive Sciences (IPS) mission is to Pioneer, Partner and Predict to drive transformative insights for patient benefit. IPS conducts applied computational research in areas that include genomic, structural and molecular informatics, computational and systems biology, patient selection and translational biomarker research, and broader fields including knowledge science, epidemiology and machine learning—across the full lifecycle of drug discovery and development and across all therapeutic areas at BMS. We do this in close partnership with scientific and clinical experts in the field, both inside and outside the company.  We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines. In doing so, our work transforms the lives of patients, as well as our own lives and careers.

Here, you’ll get the chance to grow and thrive through opportunities that are uncommon in scale and scope. You’ll pursue innovative ideas while advancing professionally alongside some of the brightest minds in biopharma.

We seek a highly innovative and collaborative machine learning scientist to join our Translational Bioinformatics Immunology, Cardiovascular and Neurology (ICN) team. This individual will contribute to our fast-growing effort to apply cutting-edge AI/ML techniques to advance BMS’s industry leading ICN programs.

The role offers unprecedented opportunity to identify unmet medical needs in complex ICN diseases and impact the discovery and prioritization of BMS’s transformational and life-changing therapies. We encourage inquiries from those with a strong background in AI/ML who also have a strong interest in innovation and interdisciplinary application of computational approaches to life sciences data.

Responsibilities

• Build and apply advanced deep learning models to construct gene/protein networks, form disease pathogenesis hypothesis and identify drug targets (e.g., using self-supervised learning, large language models, deep learning, or graph neural networks).
• Leverage ML approaches to define patient endotypes, propose precision medicine plans, and inform prioritization of target discovery.
• Analyze transcriptomics, proteomics, exome and whole genome sequencing, multiplex flow cytometry, 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.

Basic Qualifications:

• Bachelor's Degree with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field from a recognized higher-education institution 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 from a recognized higher-education institution and 5+ years of academic / industry experience
• or PhD with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field from a recognized higher-education institution and 2+ years of academic / industry experience

Preferred Qualifications:

• Ph.D. with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field from a recognized higher-education institution
• Two (2) or more years relevant experience in machine learning research. Position can be filled at a different level based on depth of experience and scientific expertise.
• Strong experience in applying contemporary deep learning methods, preferably with demonstrated application of either active, generative, graph-based, or other 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. Verbal and written English language fluency are prerequisite.