Senior Scientist, Computational Sciences – Computational Antibody Discovery and Design

Working with Us
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Job Description

We are seeking a collaborative scientist for an interdisciplinary bioinformatics and computational biology role in the Biotherapeutics Computational Design team in Cambridge, MA. This is a technically deep individual contributor role focused on building scalable analysis workflows and models for antibody discovery, with direct impact on early drug discovery in pre-clinical programs. You will develop novel bioinformatics pipelines to analyze next-generation sequencing (NGS) data and build predictive models to discover and characterize antibodies. You will partner with both computational and experimental scientists to design experiments, analyze data, and implement computational models and bioinformatics pipelines. This role provides the opportunity to work on cross-functional teams to solve challenging problems and help advance the next generation of biotherapeutics at Bristol Myers Squibb.

Responsibilities

• Own end-to-end computational workflows supporting antibody hit discovery and lead prioritization in pre-clinical programs.
• Implement and deploy high-throughput and scalable bioinformatics pipelines to analyze antibody repertoire sequencing and selection NGS data (such as in vitro display or in vivo immunization) with the goal to expedite biologics discovery and design.
• Develop predictive models to analyze and characterize antibody repertoire sequencing data to deliver insights on antibody properties, assess fitness to target candidate profile, and ultimately improve lead candidate identification.
• Serve as computational science partner in antibody discovery programs, design and execute computational experiments to answer program-specific questions.
• Partner with cross-functional project teams to develop bioinformatics & machine learning solutions for novel biotherapeutics.
• Communicate scientific findings to collaborators and other stakeholders, propose follow-up actions with measurable scientific outcomes.

Qualifications

Required:

• PhD in bioinformatics, computer science, engineering, statistics, or similar with 4+ years of relevant industry experience.
• In-depth experience analyzing NGS data and building scalable bioinformatics pipelines.
• In-depth understanding of antibody sequence and structure.
• Strong experience with commonly used bioinformatics methods and toolkits for tasks such as sequence alignment, clustering, annotation, and exploratory analysis.
• Strong experience with scientific programming languages (Python, R) and data science libraries.
• Ability to independently conduct scientific research, develop hypotheses, and deliver functional and sustainable solutions without technical debt.
• Excellent problem-solving skills and teamwork.
• Strong communication, documentation, and presentation skills.

Preferred:

• In-depth experience analyzing NGS data, specifically B-cell receptor repertoires from mice immunization campaigns and synthetic repertoires from in vitro display technologies.
• Proven experience building large-scale complex workflows using established workflow orchestrators such as CWL, WDL, Nextflow for high-throughput data analysis.
• Experience with state-of-the-art AI/ML methods applied to biological sequence data such as protein language models, structure prediction models, developability and biophysical property prediction models.
• Hands-on experience with public protein and immune repertoire resources such as PDB, OAS, and SAbDab.
• Proven track record of effective collaboration in multi-disciplinary team projects.

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