Principal Scientist, Predictive Sciences (Cell Therapy Predictive Sciences)

Redwood City, California
Jul 31, 2021
Required Education
Position Type
Full time

At Bristol Myers Squibb, we are inspired by a single vision – transforming patients’ lives through science. In oncology, hematology, immunology and cardiovascular disease – and one of the most diverse and promising pipelines in the industry – each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.

We hire the best people and provide them with a work environment that places a premium on diversity, integrity, collaboration and personal development. Through a culture of inclusion, we create a better, more productive work environment. We believe that the diverse experiences and perspectives of all our employees help to drive innovation and transformative business results.


We seek an enthusiastic, collaborative data scientist with strong expertise in machine learning to work on cross-asset questions in cellular immunotherapy to help us further optimize our cell therapy products for improved patient outcomes. The successful applicant is expected to play a key role partnering with several internal manufacturing and research teams to help develop and deploy next generation cellular therapies.

The candidate will closely collaborate with Cell Therapy Development and Operations (CTDO) colleagues in Seattle and New Jersey, and work cross-functionally with global IPS colleagues, Research and Early Development (R&ED), the Immuno-Oncology and Cellular Therapy Thematic Research Center (IO/CT TRC), Clinical Development, and Global Biometrics and Data Science (GBDS). Keen interest and hands-on expertise in the inter-disciplinary application of advanced statistical learning methods to life sciences, CMC and clinical datasets are imperative. We are deeply passionate about what we do here at BMS, because we know that our work helps deliver truly innovative and life-changing therapies for complex diseases of unmet medical need—if this inspires you as well, we’re excited to have you join us!


Working in collaboration with computational, biological and clinical scientists across the Bristol Myers Squibb IPS, CTDO, GBDS, and IO/CT organizations, responsibilities include but are not limited to:

  • Develop and apply state-of-the-art algorithmic and data-driven statistical learning approaches to identify patient and product phenotypes associated with positive clinical and manufacturing outcomes and generate predictive models to guide manufacturing process development and decision making
  • Develop novel integrative analysis strategies for high content, high-throughput cell imaging and molecular profiling data sets including bulk and single cell RNA-seq, ATAC-seq, CITE-Seq, and high-dimensional flow cytometry to define critical manufacturing attributes
  • Enhance the interpretability of our machine learning predictions using variable attribution and sparse local effect decomposition methods
  • Engage with colleagues and as part of project teams passionate about developing the next generation of innovative cell therapies, lending analytics expertise to biological and technical subject matter experts as required
  • Present strategies, approaches, results and conclusions to a publishable standard in static and interactive formats
  • Stay informed on the latest research in machine learning methods and analyze their potential impact on our capabilities
  • Participate in authorship of scientific reports, and present methods and conclusions to publishable standards


  • PhD degree and 5 years experience or MS and 7 years experience in machine learning, statistics, computer science, computational biology or related data science fields with a strong publication record demonstrating statistical learning expertise on high-dimensional data sets.
  • Demonstrated ability to derive insights from high-dimensional data with complex patterns using statistical learning approaches using readable, reproducible, and efficient code
  • Demonstrated ability to analyze and infer molecular mechanisms from bulk and single cell NGS data (e.g., RNA-seq, ATAC-seq, immune sequencing)
  • Expertise in application of statistical learning methods and familiarity with the underlying theory, statistical programming and data manipulation using R or Python; contemporary, open-source bioinformatics tools and database structures, collaborative development skills using version control systems (e.g. Git), familiarity with Unix shell and deployment and use of virtualized working environments (e.g. Docker)
  • Proven problem-solving skills, collaborative nature and flexibility across multiple research domains
  • Ability to work independently and also as a member of a global analytical research team in a fast-paced environment
  • Familiarity with cell biology, immunology, oncology, or biologics a plus
  • Fluent verbal and written English language skills

Around the world, we are passionate about making an impact on the lives of patients with serious diseases. Empowered to apply our individual talents and diverse perspectives in an inclusive culture, our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.

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. 

Our company is committed to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace adjustments and ongoing support in their roles. Applicants can request an approval of accommodation prior to accepting a job offer. If you require reasonable accommodation in completing this application, or any part of the recruitment process direct your inquiries to Visit to access our complete Equal Employment Opportunity statement.