Senior Scientist, Computational Sciences - Computational Antibody Discovery and Design

Bristol Myers Squibb
Boston, US
On-site

Job Description

Working with Us

Challenging. Meaningful. Life-changing. Those aren't words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You'll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

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 .

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.

If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

Compensation Overview:

Cambridge Crossing: $148,210 - $179,601

The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job

Skills & Requirements

Technical Skills

PythonRNgs data analysisBioinformatics pipelinesAntibody sequence and structureBiotechnologyComputational biology

Salary

$148,210 - $179,601

year

Employment Type

FULL TIME

Level

senior

Posted

4/30/2026

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