Senior Scientist, Machine Learning

Key Skills

Aartificial intelligence, Analytical and Problem solving, Bioinformatics, Deep Learning, Drug Discovery, Effective communication skills, Keras software library, Machine learning techniques, PyTorch, 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 collaborative and highly innovative computational scientist to join our Predictive Sciences team and develop predictive models using cutting-edge machine learning/artificial intelligence techniques to discover novel therapeutic opportunities.

This position will work alongside colleagues in Informatics & Predictive Sciences (IPS), Protein Homeostasis, Small Molecule Drug Design and other teams in BMS Research, and play a key scientific role in shaping the future of our most advanced therapeutic approaches, primarily focusing on protein degradation, to pursue opportunities beyond the reach of conventional small molecules. We welcome applications from candidates who are passionate about learning new drug discovery paradigms, bringing new medicines to the patients, and comfortable working in a fast-paced and highly collaborative environment.

Responsibilities:

• Interrogate properties of protein-protein and protein-ligand interaction surfaces and their molecular representations.
• Develop and apply state-of-the-art artificial intelligence/machine learning algorithms, including geometric deep learning and graph-based models, to predict complex biomolecular interactions and their selectivity.
• Devise AI/ML strategy to predict, or de novo design, small molecule ligands that enhance complex protein-protein interaction interfaces.
• Design experiments to elucidate protein interactions at the molecular level, process and analyze data for model training or to validate findings.
• Communicate results and findings to scientific project teams and stakeholders.
• Contribute to planning and execution of collaborative projects with leading academic and commercial research groups worldwide.

Basic Qualifications:

• Bachelor's Degree in computer science, bioinformatics, machine learning or computational biology and 7+ years of academic / industry experience
• or Master's Degree in computer science, bioinformatics, machine learning or computational biology and 5+ years of academic / industry experience
• or PhD in computer science, bioinformatics, machine learning or computational biology 2+ years of academic / industry experience

Preferred Qualifications:

• Ph.D. in machine learning with 2+ years of post-doctoral experience in applying computational and analytical approaches in university, pharma, or biotech settings.
• Expertise in developing state-of-the-art deep learning techniques, including diffusion models and large language models.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras, including underlying implementations.
• Demonstrated ability to design & engineer multiple molecular representations and apply predictive, multivariate research approaches to integrated molecular and chemistry datasets.
• Strong working knowledge of protein structure/folding and protein-ligand interaction prediction.
• Strong problem-solving skills and ability to work independently and as part of a team.
• Excellent communication and interpersonal skills.

The starting compensation for this job is a range from $109,000 to $150,700, plus incentive cash and stock opportunities (based on eligibility).

The starting pay rate takes into account characteristics of the job, such as required skills and where the job is performed.

Final, individual compensation will be decided based on demonstrated experience.

Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit our BMS Career Site.