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 rich in diversity. 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 .

SUMMARY:

Partner with scientists within the Research organization to explore how the latest technologies can accelerate and transform scientific discovery and research processes. Experiment and apply new analytical artificial intelligence (AI) and generative artificial intelligence (GenAI) technologies to enhance how research data and knowledge is generated and ultimately disseminated. Collaborate with Research laboratory and computational scientists along with the broader Business Insights & Technologies organization to support the discovery of innovative medicines that help patients prevail over serious disease.

Responsibilities:

• Partner and collaborate as part of a matrix-ed team to explore how analytical and generative AI technologies can impact Research focus areas including but not limited to knowledge management, document generation, and laboratory operations
• Design and develop Large Language Model (LLM) based applications through generating, optimizing and documenting clean and efficient code
• Experiment with new digital technologies through use case rapid prototyping related to areas such as knowledge search, extraction, and summarization in close collaboration with Research and Business Insights & Technology stakeholders
• Participate in internal and external opportunities to share scientific and technical thought leadership and communicate technical lessons learned

Skills/Experience:

• A Bachelors or higher degree in a scientific or engineering field with 1-3 years of experience in a scientific informatics, biopharma or an academic organization
• Hands on code generation, optimization and review experience (python preferred but R, SQL and others relevant too)
• Familiarity interacting with different API protocols, especially OpenAI API endpoints and deploying cloud and data engineering tools (AWS, GCP, Azure services)
• Experience with building and applying AI, Machine Learning (ML) and/or LLM techniques such as prompt engineering, RAG workflows including vector embeddings, supervised/ unsupervised / reinforcement learning, natural language processing (NLP) and model training / fine tuning
• Familiarity with diverse biomedical and data types (structured research data, unstructured study reports, semi-structured project presentations, etc.) along with different data management practices (e.g. knowledge graphs) a plus
• An understanding of common research scientific platforms (e.g. electronic lab notebooks (ELNs), Laboratory Information Management Systems (LIMS), etc.) a plus
• A curious and inquisitive mindset, strong listening and communication skills and an ability to adapt quickly within a rapidly evolving environment

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.

• Partner and collaborate as part of a matrix-ed team to explore how analytical and generative AI technologies can impact Research focus areas including but not limited to knowledge management, document generation, and laboratory operations
• Design and develop Large Language Model (LLM) based applications through generating, optimizing and documenting clean and efficient code
• Experiment with new digital technologies through use case rapid prototyping related to areas such as knowledge search, extraction, and summarization in close collaboration with Research and Business Insights & Technology stakeholders
• Participate in internal and external opportunities to share scientific and technical thought leadership and communicate technical lessons learne