Software Development Engineer III, AI Data Engineering

Bristol-Myers Squibb; United States; On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Health benefits

Job summary

Bristol Myers Squibb is seeking an AI Data Science Engineer to advance AI-driven insights within the Global Market Access and HEOR IT function. You will develop AI-powered solutions and ML pipelines, collaborating with business and IT to scale models and deliver data-driven decisions.

The role emphasizes foundation models, prompt engineering, and deployment across cloud environments (AWS), with a focus on governance and impactful outcomes for patient access and value demonstration.

Qualifications

• Requires advanced knowledge in data & analytics and a university degree, plus 6+ years of experience.
• Experience with data provisioning, data mining, data visualization, machine learning, coding in Python/R, and cloud platforms like AWS.

Responsibilities

• Develop and deliver AI-powered solutions to bring medicines to patients faster.
• Develop ML pipelines that can evolve rapidly with new modeling approaches.
• Partner with business and IT to scale and operationalize AI solutions for business goals.

Skills

Data analytics

Python

GitHub

ML frameworks

AWS

LLM solutions

Prompt engineering

Foundation models

Vector databases

MLFlow

Pytorch

TensorFlow

Education

University degree

Tools

MLFlow

Pytorch

TensorFlow

Job description

At Bristol Myers Squibb, our employees often ask, "Who are you working for?"-a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

Position Summary

At BMS, digital innovation and Information Technology are central to our vision of transforming patients' lives through science. To accelerate our ability to serve patients around the world, we must unleash the power of technology. We are committed to being at the forefront of transforming the way medicine is made and delivered by harnessing the power of computer and data science, artificial intelligence, and other technologies to promote scientific discovery, faster decision making, and enhanced patient care. The AI Data Science Engineer will play a key role in strategic use of data and artificial intelligence to drive critical business impacts through the delivery of data-driven insights in the Global Market Access and HEOR IT function.

If you want an exciting and rewarding career that is meaningful, consider joining our diverse team!

Key Responsibilities

• Develop and deliver AI-powered solutions that will bring more medicines to more patients faster
• Develop ML pipelines that can evolve rapidly to incorporate new and/or more effective modeling approaches
• Partner with business and IT groups to scale and operationalize AI solutions to advance business goals and gain competitive advantage
• Engage a broader community to help educate the business on the practical application of AI to drive business value and widespread adoption
• Serve as a knowledge expert in foundation models and communicate insights, recommendations, value and impact to technical and non-technical stakeholders
• Stay up-to-date with emerging trends in data science and machine learning, and apply that knowledge to drive innovation within the organization

Qualifications & Experience

• Requires advanced knowledge applicable to a wide range of work in data & analytics and thorough knowledge of other functions, typically gained through a university degree and 6+ years of experience .
• Demonstrates knowledge in data & analytics skillsets such as data provisioning, data mining, data visualization, machine learning, code development in python/R, Github, cloud computing platforms like AWS, model governance with MLFlow or equivalent.
• Potential to lead initiatives related to implementation of new technologies, especially LLM-based solutions.
• Can package information and data that tells a story and provides insight to a broader problem. Presents and explain the implications of key information on issues important to the business unit.
• Frequently interacts with other internal and external stakeholders regarding operational decisions and business requirements. Analyzes the impact of conclusions and actions on people, technology, structure, and workflow across teams
• Gives others challenging opportunities to build strong capabilities for team. Helps drive a culture which motivates awareness and learning through creating space for conversations and debate.
• Demonstrates a focus on improving processes, structures, and knowledge within the team. Leads in analyzing current states, deliver strong recommendations in understanding complexity in the environment, and the ability to execute to bring complex solutions to completion.
• Stays current with emerging trends in specialty area. Identifies future state and dimensions of change (org, tech, cultural) to achieve. Creates transition plans for new processes, implements and monitor's change. Ensures alignment of plans with the enterprise's strategic vision and translates the vision to connect to team's work
• Maintains a broad perspective when analyzing information and utilizes analytical thought while pushing others to do the same, considering long-term implications. Uses judgement and creativity in structuring work and finding solutions that are not obvious. Reviews and assess solutions proposed by others to determine the best path moving forward.

Required Knowledge and Skills

• Developing and deploying generative AI solutions.
• Programming in Python and hands-on experience with frameworks such as Pytorch or Tensorflow.
• Prompt engineering and vector databases.
• Work with unstructured and semi-structured data.
• Fine-tuning deep learning models.
• Familiarity with a cloud environment (AWS/GCP/Azure).
• MLOps principles and model development lifecycle.

Desirable Experience

• Building RAG pipelines, chat applications and implementing AI agents.
• Frameworks such as LlamaIndex and LangChain.
• Leveraging Hugging Face models.
• Familiarity with vision models.